A method for predicting cavitation erosion considering cavity collapse and its energy transport process

Abstract

The present application relates to a kind of cavity erosion prediction method considering cavity collapse and its energy transport process, belong to the technical field of hydrodynamics research.The cavity erosion prediction method includes the following steps: solving cavitation flow field to the object to be predicted;Based on the physical property change of cavity collapse, identify collapse region and record cavity collapse pressure;According to cavity collapse pressure, calculate collapse energy;Analysis of the transport process of collapse energy radiated to the wall to be predicted position, calculate transfer parameter and attenuation parameter, and the transport parameter is obtained by multiplication;Combined with collapse energy and transport parameter, calculate the cavity erosion load of collapse energy radiated to the wall, and the cumulative cavity erosion load of the current predicted position of wall is obtained by accumulation;According to cumulative cavity erosion load, determine the cavity erosion region.The cavity erosion prediction method considers the real physical process of cavity collapse, ensures the authenticity of collapse region identification, and considers the transfer and dissipation process in energy transport, ensures the accuracy of cavity erosion region prediction.

Description

Technical Field

[0001] This invention belongs to the field of hydrodynamics research technology, and in particular relates to a method for predicting cavitation erosion that considers cavity collapse and its energy transport process. Background Technology

[0002] Cavitation is a fluid dynamics phenomenon caused by the local pressure of water flow falling below the saturated vapor pressure at the same state and temperature, leading to the initial formation, development, and collapse of cavitation bubbles, and triggering a series of complex physical processes. Cavitation erosion refers to the phenomenon where cavitation bubbles, after entering a high-pressure zone with the liquid flow, rapidly collapse, generating microjets and shock waves, causing mechanical erosion and chemical corrosion to solid surfaces. Such cavitation and cavitation erosion phenomena not only occur in fluid machinery and hydraulic engineering but also frequently appear in underwater weapons and equipment. Furthermore, with increasing water flow velocity, cavitation and collapse cavitation erosion become more complex and severe, thus affecting the long-term stable operation of equipment. Therefore, suppressing or mitigating cavitation erosion is one of the keys to improving equipment stability, and this is also a significant technical bottleneck facing my country's development of marine equipment.

[0003] Currently, large-scale cavitation experiments on marine equipment suffer from high costs and long cycles, hindering rapid upgrades and iterations of equipment models. Numerical simulation methods, however, can quickly obtain cavitation flow fields and cavitation erosion results. Most existing cavitation erosion prediction methods directly calculate the cavity collapse energy on the wall. However, as is well known, when a cavity collapses in a flow field, flow characteristics and physical parameters undergo abrupt changes, and the cavitation bubble rapidly collapses and condenses into liquid, releasing enormous pressure. Existing cavitation erosion prediction methods that directly calculate the cavity collapse energy on the wall do not consider the physical process of cavity collapse, leading to inaccurate assessments of the collapse location. Furthermore, after cavity collapse, not all of the initial energy contained within the collapse can radiate to the wall; energy attenuation is inevitable during this transport process. Existing cavitation erosion prediction methods that directly calculate the cavity collapse energy on the wall also ignore this attenuation during energy transport, resulting in poor reliability and low accuracy.

[0004] Therefore, how to provide a more reliable and accurate method for predicting cavitation erosion is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a cavitation erosion prediction method that considers cavity collapse and its energy transport process. This cavitation erosion prediction is based on the actual collapse physical process, enabling precise identification of the collapse location and ensuring accurate input of collapse energy. Furthermore, the cavitation erosion prediction also considers energy transport efficiency and dissipation, accurately calculating the cavitation load on the wall surface and ensuring the real output of collapse energy, thereby guaranteeing the reliability and accuracy of the cavitation erosion prediction results.

[0006] This invention provides a method for predicting cavitation erosion that considers cavity collapse and its energy transport process, comprising the following steps:

[0007] Solving the cavitation flow field: Divide the computational domain of the object to be predicted and draw the mesh of the computational domain, then solve the cavitation flow field;

[0008] Determine the collapse region and collapse pressure: Based on the obtained cavitation flow field, obtain the physical characteristic values ​​of each grid cell at each time. Based on the changes in physical characteristics when cavity collapse occurs, identify the collapse region where cavity collapse occurs at each time and record the cavity collapse pressure of each collapse region.

[0009] Calculate the collapse energy: For each collapse zone, calculate the collapse energy per unit time and per unit volume of that collapse zone based on the cavity collapse pressure. ;

[0010] Calculate the collapse energy transport parameters: For each collapse region, calculate the transport parameters of the collapse energy radiation from that region to the predicted location on the wall. and attenuation parameters According to the formula The transport parameters of the collapse energy radiation from the collapse zone to the predicted location on the wall were calculated. ;

[0011] Calculate the cavitation load on the wall surface: For each location on the wall to be predicted, according to the formula... The cavitation load is calculated as follows: the cavitation energy radiated from each cavitation region per unit time and unit volume to the current predicted location on the wall. The cavitation load on the wall at the current predicted location is obtained by summing the collapse energy radiated from all collapse regions in the computational domain at the current moment to the wall at the current predicted location. The cumulative cavitation load at the current predicted position of the wall is obtained by summing the cavitation loads at all times during the operating cycle of the object to be predicted. ;

[0012] Predicted cavitation zone: based on the cumulative cavitation load at each location to be predicted on the wall surface. Determine the cavitation erosion area.

[0013] In some embodiments, the specific steps for solving the cavitation flow field are as follows: setting boundary conditions that satisfy physical reality at the boundary of the computational domain, solving the mass conservation equation and momentum conservation equation satisfied by the fluid motion in the computational domain, and solving the multiphase flow equation satisfied by the fluid cavitation evolution in the computational domain, to obtain the cavitation flow field.

[0014] In some embodiments, the specific step of identifying the collapse region in the steps of determining the collapse region and collapse pressure is as follows: when the physical property value corresponding to the mesh cell satisfies and and When this occurs, the grid cell is determined to be a collapse region where cavity collapse has occurred; among which, It represents the vapor phase volume fraction. For water vapor mass transport rate, This is the derivative of local pressure with respect to time.

[0015] In some embodiments, the collapse energy calculation step involves calculating the collapse energy of the collapse region per unit time and per unit volume. The calculation formula is:

[0016]

[0017] In the formula, The cavity collapse pressure in the collapse zone, This is the saturated vapor pressure of liquid water. and These are the densities of water vapor and water liquid, respectively. It represents the vapor phase volume fraction. This refers to the water vapor mass transport rate.

[0018] In some embodiments, in the step of calculating the collapse energy transport parameters, the transfer parameters are... The calculation formula is:

[0019]

[0020] In the formula, Let be the spatial vector from the collapse region to the predicted location on the wall surface. Let be the normal vector at the location on the wall to be predicted.

[0021] In some embodiments, in the step of calculating the collapse energy transport parameters, the attenuation parameter... The calculation formula is:

[0022]

[0023] In the formula, For control parameters, This represents the volume fraction of the vapor phase.

[0024] In some embodiments, the specific step of determining the cavitation erosion region in the step of predicting the cavitation erosion region is as follows: comparing the cumulative cavitation erosion load at each location to be predicted on the wall surface. The magnitude of the preset load threshold for cavitation erosion, when the cumulative cavitation load... If the load is greater than or equal to the preset load threshold, the predicted location is determined to be a cavitation area.

[0025] In some embodiments, the preset load threshold is 5 kW / m. 2 .

[0026] Compared with the prior art, the advantages and beneficial effects of the present invention are as follows:

[0027] 1. The cavitation erosion prediction method considering cavity collapse and its energy transport process provided by the present invention identifies the collapse region based on the real physical process. Starting from the changes in physical characteristics when cavity collapse occurs, it provides a reliable and simple method for identifying the cavity collapse region of the cavitation flow field. At the same time, using the cavity collapse pressure corresponding to the accurately identified collapse region as the collapse energy input can ensure the accuracy of subsequent predictions.

[0028] 2. In the cavitation erosion prediction method considering cavity collapse and its energy transport process provided by the present invention, the calculation of cavitation erosion load introduces the collapse energy transport parameter. This parameter not only considers the energy transfer efficiency on the transport path, but also the energy attenuation caused by cavity scattering on the transport path, thereby improving the accuracy of the cavitation erosion prediction method from the perspective of energy transport.

[0029] 3. The cavitation erosion prediction method considering cavity collapse and its energy transport process provided by this invention has a solid physical basis, a wide range of applications, and accurate prediction results. Attached Figure Description

[0030] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0031] Figure 1 A flowchart of a cavitation erosion prediction method considering cavity collapse and its energy transport process, provided in an embodiment of the present invention;

[0032] Figure 2 A flowchart illustrating the identification of collapse regions in a cavitation erosion prediction method considering cavity collapse and its energy transport process, provided in an embodiment of the present invention.

[0033] Figure 3 This is a schematic diagram of the structure and computational domain of the axisymmetric nozzle to be predicted in Embodiment 1 of the present invention;

[0034] Figure 4 This is a comparison chart of the cavitation region prediction results of Embodiment 1 of the present invention with the prediction results of existing real-size cavitation experiments and existing numerical simulation prediction methods.

[0035] In the picture:

[0036] 1. Entrance; 2. Exit. Detailed Implementation

[0037] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] As attached Figure 1 As shown, in an illustrative embodiment of the cavitation erosion prediction method of the present invention, which considers cavity collapse and its energy transport process, the cavitation erosion prediction method includes the following steps:

[0039] S1 Solving the cavitation flow field: Divide the computational domain of the object to be predicted and draw the mesh of the computational domain, then solve the cavitation flow field;

[0040] S2 Determine the collapse region and collapse pressure: Based on the obtained cavitation flow field, obtain the physical characteristic values ​​of each grid cell at each time. Based on the changes in physical characteristics when cavity collapse occurs, identify the collapse region where cavity collapse occurs at each time and record the cavity collapse pressure of each collapse region.

[0041] S3 calculates the collapse energy: For each collapse zone, the collapse energy per unit time and per unit volume of that zone is calculated based on the cavity collapse pressure. ;

[0042] S4 Calculates Collapse Energy Transport Parameters: For each collapse region, calculates the transport parameters during the collapse energy radiation from that region to the predicted location on the wall. and attenuation parameters According to the formula The transport parameters of the collapse energy radiation from the collapse zone to the predicted location on the wall were calculated. ;

[0043] S5 calculates the cavitation load on the wall surface: For each location on the wall to be predicted, according to the formula... The cavitation load is calculated as follows: the cavitation energy radiated from each cavitation region per unit time and unit volume to the current predicted location on the wall. The cavitation load on the wall at the current predicted location is obtained by summing the collapse energy radiated from all collapse regions in the computational domain at the current moment to the wall at the current predicted location. The cumulative cavitation load at the current predicted position of the wall is obtained by summing the cavitation loads at all times during the operating cycle of the object to be predicted. ;

[0044] S6 Predicted Cavitation Area: Based on the cumulative cavitation load at each location to be predicted on the wall surface. Determine the cavitation erosion area.

[0045] The aforementioned cavitation erosion prediction method, which considers cavity collapse and its energy transport process, identifies the collapse region based on real physical processes. Starting from the changes in physical characteristics during cavity collapse, it provides a reliable and concise method for identifying cavity collapse regions in the cavitation flow field. Furthermore, using the cavity collapse pressure corresponding to the accurately identified collapse region as the collapse energy input ensures the accuracy of subsequent predictions. In addition, the method incorporates a collapse energy transport parameter into the calculation of the cavitation erosion load. This parameter considers not only the energy transfer efficiency along the transport path but also the energy attenuation caused by cavity scattering along the transport path, thus improving the accuracy of the cavitation erosion prediction method from the perspective of energy transport. In summary, the aforementioned cavitation erosion prediction method, which considers cavity collapse and its energy transport process, has a solid physical basis, a wide range of applications, and accurate prediction results.

[0046] The S1 step for solving the cavitation flow field involves the following steps: setting physical boundary conditions at the computational domain boundary; solving the mass and momentum conservation equations for fluid motion within the computational domain, as well as the multiphase flow equations for cavitation evolution of the fluid within the computational domain; and obtaining the cavitation flow field. It should be noted that the mesh generation of the computational domain and the solution of the cavitation flow field in the S1 step can be performed using Fluent software. The mesh generation of the computational domain can be selected based on the shape of the computational domain, choosing from hexahedral, tetrahedral, and hybrid meshes, etc. When solving the cavitation flow field, the boundary conditions are set based on the actual physical conditions that the fluid needs to satisfy when moving within the object to be predicted. These mainly involve setting boundary conditions for the computational domain inlet, outlet, and walls, including flow rate, pressure, and slip boundary conditions.

[0047] like Figure 2 As shown, in step S2, which determines the collapse region and collapse pressure, the specific steps for identifying the collapse region are as follows: when the physical property values ​​corresponding to the mesh element satisfy... and and When this occurs, the grid cell is determined to be a collapse region where cavity collapse has occurred; among which, It represents the vapor phase volume fraction. For water vapor mass transport rate, For local pressure on time The derivative of . It should be noted that when a cavity collapses in the flow field, the cavitation bubble rapidly collapses and condenses into liquid, releasing enormous pressure in the process. and This proves that steam condensation occurs in the grid cell, thus identifying the steam condensation region. The fact that the current pressure is significantly higher than the previous pressure proves that a huge pressure was released instantaneously, confirming that the steam condensation in this area is caused by the collapse of the cavity, rather than by the migration and transport of the cavity. Therefore, the collapse area can be accurately identified by simultaneously satisfying the three conditions for cavity collapse. It should also be noted that each grid cell needs to be judged one by one. If the current grid cell cannot simultaneously satisfy the three conditions for cavity collapse, it is considered that no collapse has occurred at that location, and then the cavity collapse identification is performed on the next grid cell.

[0048] In the S3 step of calculating collapse energy, the collapse energy of the collapse region per unit time and per unit volume is... The calculation formula is:

[0049] (1)

[0050] In equation (1), The cavity collapse pressure in the collapse zone, This is the saturated vapor pressure of liquid water. and These are the densities of water vapor and water liquid, respectively. It represents the vapor phase volume fraction. This refers to the water vapor mass transport rate.

[0051] It should be noted that, within the framework of energy level theory, the collapse energy is considered to be caused by the high-pressure shock wave generated by the collapse of the cavity structure, and the potential energy of the collapse is... It is expressed as the product of the high-pressure impact force and the volume occupied by the cavity. ,Right now:

[0052] (2).

[0053] By taking the volume derivative of equation (2) and dividing it by the total volume of the cavity region, the collapse energy per unit time and per unit volume can be obtained. By further combining the mass conservation equation and the multiphase flow equation for simplification, we can obtain the expression for the collapse energy, which depends on the local fluid characteristics and the water vapor mass transport rate, as shown in equation (1).

[0054] It should also be noted that the area of ​​collapse The negative value represents the transfer from the vapor phase to the liquid phase, corresponding to the process of cavity collapse and vapor condensation. Therefore, in equation (1), the negative value indicates that the vapor phase is transferred to the liquid phase. Take the opposite number.

[0055] In the S4 step of calculating collapse energy transport parameters, the transfer parameters... The calculation formula is:

[0056] (3)

[0057] In equation (3), Let be the spatial vector from the collapse region to the predicted location on the wall surface. Let be the normal vector at the location on the wall to be predicted.

[0058] It should be noted that the collapse energy radiates outwards in the form of a high-pressure spherical wave until it reaches the wall, forming a cavitation phenomenon. During this process, the energy transfer efficiency along the transport path needs to be considered. The transfer parameters depend on the distance from the collapse cavity to the wall and the angle at which the energy radiates to the wall. Therefore, a spatial vector from the collapse region to the predicted location on the wall is introduced. and the normal vector at the location to be predicted on the wall The transfer parameters are obtained as shown in equation (3). The expression.

[0059] In the S4 step of calculating the collapse energy transport parameters, the attenuation parameter... The calculation formula is:

[0060] (4)

[0061] In equation (4), For control parameters, This represents the volume fraction of the vapor phase.

[0062] It should be noted that during the process of transporting collapse energy to the wall, the attenuation of energy due to cavity scattering along the transport path also needs to be considered, and the attenuation parameter... The attenuation parameter, as shown in equation (4), is established based on the vapor volume fraction along the transport path. The expression is given. The control parameters can be calibrated using experimental data or given based on experience.

[0063] Combining the above transmission parameters Calculation formula and attenuation parameter The calculation formula yields the transport parameters. The calculation formula is:

[0064] (5).

[0065] In step S5, the cavitation load on the wall surface is calculated using the following formula (6): the cavitation load radiated by the collapse energy per unit time and per unit volume to the current predicted position of the wall surface is calculated. It can utilize transport parameters Correct the cavitation load to ensure that the output of the collapse energy is real.

[0066] (6).

[0067] It should be noted that the cavitation load at the current predicted location of the wall surface at the current moment is... The calculation formula is:

[0068] (7)

[0069] In equation (7), It represents the total volume of all collapse regions where cavitation occurs within the cavitation flow field.

[0070] Cumulative cavitation load at the current predicted location of the wall surface The calculation formula is:

[0071] (8)

[0072] In equation (8), The running cycle of the object to be predicted.

[0073] In the S6 step of predicting cavitation erosion areas, the specific steps for determining the cavitation erosion areas are as follows: compare the cumulative cavitation loads at each location to be predicted on the wall surface. The magnitude of the preset load threshold for cavitation erosion, when the cumulative cavitation load... When the load is greater than or equal to a preset load threshold, the predicted location is determined to be a cavitation erosion area. Preferably, the preset load threshold is 5 kW / m. 2 .

[0074] To provide a clearer and more detailed description of the cavitation erosion prediction method considering cavity collapse and its energy transport process provided by the embodiments of the present invention, the following description will be based on specific embodiments.

[0075] Example 1

[0076] Taking the axisymmetric nozzle in marine equipment and machinery as the object to be predicted, the structure of the axisymmetric nozzle is as follows: Figure 3 As shown, it has a long and narrow constriction section with a very high flow velocity, resulting in very low local pressure and frequent cavitation erosion. Therefore, an axisymmetric nozzle was selected as the object to be predicted to study its cavitation erosion.

[0077] (1) Solving for the cavitation flow field

[0078] This step is performed using Fluent software, as detailed below:

[0079] First, for the axisymmetric nozzle model under study, a corresponding computational domain is divided inside the nozzle, and a high-quality hexahedral mesh is drawn within the computational domain. In particular, the mesh is refined for the strong shear region near the wall and the flow separation region at the geometric change point to ensure the accuracy of numerical calculation and the stability of the calculation process.

[0080] Furthermore, referring to the existing experimental procedures for real-scale cavitation experiments on axisymmetric nozzles (see the journal article J. Franc, Incubation Time and Cavitation Erosion Rate of Work-Hardening Materials, ASME. J. Fluids Eng. 131 (2009) 021303, https: / / doi.org / 10.1115 / 1.3063646.), boundary conditions consistent with the experiment and satisfying physical reality were set. Specifically, the circular surface at the inlet of the computational domain was set as mass flow inlet 1 with a mass flow rate of 6.25 L / s and a pressure of 21.3 bars; the annular surface at the outlet of the computational domain was set as pressure outlet 2 with a pressure of 10.1 bars; and the wall region of the computational domain was set as a no-slip boundary condition.

[0081] Finally, the finite volume method is used to solve the mass conservation equation and momentum conservation equation satisfied by the fluid motion in the computational domain, as well as the multiphase flow equation satisfied by the cavitation evolution of the fluid in the computational domain. The time step for the unsteady solution is taken as 0.00001s, and the cavitation flow field of the axisymmetric nozzle is obtained.

[0082] (2) Determine the collapse area and collapse pressure

[0083] Based on the obtained cavitation flow field, the physical characteristic values ​​of each grid cell at each time step are obtained. t Under the following conditions, when the physical property values ​​corresponding to the mesh cells satisfy... and and When the time is right, the grid cell is determined to be at that moment. t Record the cavity collapse pressure in each collapse zone where cavity collapse occurs. ;

[0084] (3) Calculate the collapse energy

[0085] For each collapse region, based on the relationship between cavity potential energy, cavity volume, and the impact force generated by cavity collapse, and combined with the mass conservation equation and multiphase flow equation, the collapse energy per unit time and per unit volume of the collapse region is calculated by the following equation (1). .

[0086] (1)

[0087] In equation (1), The cavity collapse pressure in the collapse zone, This is the saturated vapor pressure of liquid water. and These are the densities of water vapor and water liquid, respectively. It represents the vapor phase volume fraction. This refers to the water vapor mass transport rate.

[0088] (4) Calculate the collapse energy transport parameters

[0089] For each collapse zone, the transport process of collapse energy radiation from the collapse zone to the predicted location on the wall is analyzed. The transfer parameters of the transport process of collapse energy radiation from the collapse zone to the predicted location on the wall are calculated by the following equations (3) and (4). and attenuation parameters Then, the transport parameters of the collapse energy radiation from the collapse region to the predicted location on the wall are calculated according to the following formula (5). ;

[0090] (3)

[0091] (4)

[0092] (5)

[0093] In equations (3)-(5), is the spatial vector from the collapse region to the predicted location on the wall surface; This is the normal vector at the location on the wall to be predicted. To control the parameter, the value is set to 1 based on experience in this embodiment; This represents the volume fraction of the vapor phase.

[0094] (5) Calculate the cavitation load on the wall surface.

[0095] For each location on the wall to be predicted, the cavitation load radiated from the collapse energy of each collapse region to the current predicted location on the wall per unit time and per unit volume is calculated according to the following formula (6). .

[0096] (6)

[0097] Furthermore, the cavitation load on the current predicted position of the wall is obtained by summing the collapse energy radiation from all collapse regions in the computational domain to the current predicted position of the wall at the current moment according to the following equation (7). .

[0098] (7)

[0099] In equation (7), It represents the total volume of all collapse regions where cavitation occurs within the cavitation flow field.

[0100] Furthermore, the cumulative cavitation load at the current predicted position of the wall is obtained by summing the cavitation loads at all times during the operating cycle of the object to be predicted according to the following formula (8). .

[0101] (8)

[0102] In equation (8), In this embodiment, the runtime of the object to be predicted is taken as... .

[0103] (6) Predicting cavitation erosion areas

[0104] Based on the cumulative cavitation load at each location to be predicted on the wall surface A cloud map can be obtained, in which the darker the color, the higher the degree of cavitation erosion at that location. In this embodiment, 5kW / m is used. 2 As a preset load threshold for cavitation erosion, when the cumulative cavitation load... 5kW / m or greater 2 When the predicted location is determined to be a cavitation erosion area, it is then identified.

[0105] Considering the axisymmetric geometry of the axisymmetric nozzle, and for ease of comparison with existing technologies, results from 1 / 3 of the computational domain are presented here. Figure 4 (The yellow area represents the cumulative cavitation load.) Less than 5kW / m 2 The areas marked in red to black represent the cumulative cavitation load. Greater than or equal to 5kW / m 2 In areas where the color is darker, the cumulative cavitation load is corresponding to the area. (The larger the value), also, Figure 4The paper also presents the prediction results of existing real-scale cavitation experiments (see journal article J. Franc, Incubation Time and Cavitation Erosion Rate of Work-Hardening Materials, ASME. J. FluidsEng. 131 (2009) 021303, https: / / doi.org / 10.1115 / 1.3063646.) and existing numerical simulation prediction methods (see journal article X. Wang, J. Ma, T. Wang, Q. Sun, Numerical Prediction of Cavitation Erosion Risk Based on a New Erosion Indicator, Int. J. Numer.Methods Fluids 97 (2025) 329–344. https: / / doi.org / 10.1002 / fld.5347.).

[0106] Depend on Figure 4 As can be seen, using the cavitation erosion prediction method considering cavity collapse and its energy transport process in Embodiment 1 of the present invention, the severely cavitated area on the wall is 20~24 mm (i.e., Figure 4 The area between the two white circles), according to existing real-scale cavitation experiments, indicates that the severely cavitated area of ​​the wall is 19-24 mm, which is basically consistent with the prediction results. However, the severely cavitated area of ​​the wall predicted by existing numerical simulation methods ( Figure 4 The red area in the prediction results of existing numerical simulation methods is significantly smaller than the stripe range of the severely eroded wall area. Furthermore, because the erosion prediction method in Embodiment 1 of this invention, which considers cavity collapse and its energy transport process, truly considers the physical process of cavity collapse and the transport process of collapse energy, it does not over-predict the erosion area. For the slightly eroded area near the severely eroded area, the prediction results given in Embodiment 1 of this invention are more accurate than those of existing numerical simulation methods.

[0107] Therefore, the cavitation erosion prediction method considering cavity collapse and its energy transport process provided by the embodiments of the present invention is effective and can provide an accurate and reliable distribution of the risk area of ​​wall cavitation erosion. In the future, it can improve the theoretical basis and technical support for the study of cavitation erosion of marine equipment and machinery.

[0108] Finally, it should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0109] The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications can still be made to the specific implementation of the present invention or equivalent substitutions can be made to some technical features without departing from the spirit of the technical solutions of the present invention, and all such modifications and substitutions should be covered within the scope of the technical solutions claimed in the present invention.

Claims

1. A method for predicting cavitation erosion considering cavity collapse and its energy transport process, characterized in that, Includes the following steps: Solving the cavitation flow field: Divide the computational domain of the object to be predicted and draw the mesh of the computational domain, then solve the cavitation flow field; Determine the collapse region and collapse pressure: Based on the obtained cavitation flow field, obtain the physical characteristic values ​​of each grid cell at each time. Based on the changes in physical characteristics when cavity collapse occurs, identify the collapse region where cavity collapse occurs at each time and record the cavity collapse pressure of each collapse region. Calculate the collapse energy: For each collapse zone, calculate the collapse energy per unit time and per unit volume of that collapse zone based on the cavity collapse pressure. ; Calculate the collapse energy transport parameters: For each collapse region, calculate the transport parameters of the collapse energy radiation from that region to the predicted location on the wall. and attenuation parameters According to the formula The transport parameters of the collapse energy radiation from the collapse zone to the predicted location on the wall were calculated. ; Calculate the cavitation load on the wall surface: For each location on the wall to be predicted, according to the formula... The cavitation load is calculated as follows: the cavitation energy radiated from each cavitation region per unit time and unit volume to the current predicted location on the wall. The cavitation load on the wall at the current predicted location is obtained by summing the collapse energy radiated from all collapse regions in the computational domain at the current moment to the wall at the current predicted location. The cumulative cavitation load at the current predicted position of the wall is obtained by summing the cavitation loads at all times during the operating cycle of the object to be predicted. ; Predicted cavitation erosion area: based on the cumulative cavitation load at each location to be predicted on the wall surface. Determine the cavitation erosion area; In the step of calculating the collapse energy transport parameters, the transport parameters The calculation formula is: In the formula, Let be the spatial vector from the collapse region to the predicted location on the wall surface. This is the normal vector at the location on the wall to be predicted. The attenuation parameter The calculation formula is: In the formula, For control parameters, This represents the volume fraction of the vapor phase.

2. The cavitation erosion prediction method considering cavity collapse and its energy transport process according to claim 1, characterized in that, The specific steps for solving the cavitation flow field are as follows: set boundary conditions that satisfy physical reality at the boundary of the computational domain, solve the mass conservation equation and momentum conservation equation satisfied by the fluid motion in the computational domain, and solve the multiphase flow equation satisfied by the fluid cavitation evolution in the computational domain, so as to obtain the cavitation flow field.

3. The cavitation erosion prediction method considering cavity collapse and its energy transport process according to claim 1, characterized in that, In the steps of determining the collapse region and collapse pressure, the specific steps for identifying the collapse region are as follows: when the physical property values ​​corresponding to the mesh cells satisfy... and and When this occurs, the grid cell is determined to be a collapse region where cavity collapse has occurred; among which, It represents the vapor phase volume fraction. For water vapor mass transport rate, This is the derivative of local pressure with respect to time.

4. The cavitation erosion prediction method considering cavity collapse and its energy transport process according to claim 1, characterized in that, In the step of calculating the collapse energy, the collapse energy of the collapse region per unit time and per unit volume is... The calculation formula is: In the formula, The cavity collapse pressure in the collapse zone. This is the saturated vapor pressure of liquid water. and These are the densities of water vapor and water liquid, respectively. It represents the vapor phase volume fraction. This refers to the water vapor mass transport rate.

5. The cavitation erosion prediction method considering cavity collapse and its energy transport process according to claim 1, characterized in that, In the step of predicting the cavitation erosion region, the specific steps for determining the cavitation erosion region are as follows: comparing the cumulative cavitation erosion load at each location to be predicted on the wall surface. The magnitude of the preset load threshold for cavitation erosion, when the cumulative cavitation load... If the load is greater than or equal to the preset load threshold, the predicted location is determined to be a cavitation area.

6. The cavitation erosion prediction method considering cavity collapse and its energy transport process according to claim 5, characterized in that, The preset load threshold is 5kW / m 2 .

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