Water hammer protection valve body structure optimization design method based on multiphase flow adaptation

Abstract

This invention specifically discloses a method for optimizing the design of a water hammer protection valve body structure based on multiphase flow adaptation, belonging to the field of valve structure optimization technology. The method comprises the following steps: S1, obtaining the multiphase flow operating parameters of the valve and establishing a multiphase flow medium flow model and a water hammer pressure calculation model; S2, determining key water hammer protection indicators; S3, constructing a three-dimensional model of the valve body and determining the value range and constraints of each structural parameter; S4, establishing a multi-objective optimization model and solving for the optimal combination of structural parameters; wherein the optimization objectives are minimizing the multiphase flow resistance coefficient, minimizing the peak water hammer pressure, and minimizing the maximum stress of the valve body; and S5, verifying the optimal combination of structural parameters based on multiphase flow numerical simulation and structural strength simulation. This invention solves the problems of air resistance, blockage, and secondary water hammer under multiphase flow conditions, achieving precise quantitative optimization of the valve structure and improving the water hammer protection effect and structural stability.

Description

Technical Field

[0001] This invention relates to the field of valve structure optimization technology, and in particular to a method for optimizing the design of the body structure of a water hammer protection valve based on multiphase flow adaptation. Background Technology

[0002] Water hammer is a common destructive phenomenon in pipeline systems. Essentially, it arises from sudden changes in fluid velocity, causing a rapid conversion between kinetic and pressure energy, which in turn generates propagating pressure waves. In severe cases, it can directly lead to catastrophic accidents such as pipeline rupture, valve damage, and equipment failure, threatening the safe and stable operation of the pipeline system. Especially in multiphase flow conditions containing gas or solids, the uneven distribution and interphase slippage of the gas-liquid or solid-liquid two-phase or multiphase media further exacerbate the fluctuation amplitude of water hammer pressure, significantly reducing the protective effect of traditional water hammer protection valves and posing a severe challenge to the safe operation of multiphase flow pipeline systems.

[0003] Most existing water hammer protection valves are designed based on single-phase flow conditions, failing to adequately consider the complex flow characteristics of multiphase media. This results in poor adaptability of core structures such as valve channels, seats, and cores to multiphase flow conditions. On one hand, gaseous and solid particles in multiphase media easily accumulate within the valve body, forming gas resistance or flow channel blockage, which not only affects media flow efficiency but may also induce secondary water hammer. On the other hand, under the impact of water hammer, the uneven impact of multiphase flow can lead to stress imbalance in the valve structure, accelerating valve wear, shortening service life, and the buffer structure of traditional valves cannot dynamically adapt to multiphase flow parameters, resulting in low protection accuracy and difficulty in meeting the requirements of complex operating conditions.

[0004] Meanwhile, existing valve structure optimization methods often employ single-performance-objective optimization models, failing to achieve synergistic optimization of multiphase flow adaptability, water hammer protection performance, and structural strength. Furthermore, they lack quantitative correlation models between water hammer characteristics and valve structural parameters under multiphase flow conditions, resulting in highly arbitrary optimization designs and poor adaptability. This design approach cannot meet the water hammer protection requirements of complex multiphase flow pipeline systems in fields such as water supply and drainage, and petrochemicals. Therefore, there is an urgent need to develop a water hammer protection valve body structure optimization design method based on multiphase flow adaptability to address the shortcomings of existing design methods and improve the reliability and structural stability of valves under multiphase flow conditions. Summary of the Invention

[0005] The purpose of this invention is to propose a structural optimization design method for water hammer protection valves based on multiphase flow adaptation. By quantifying the correlation between multiphase flow conditions and water hammer characteristics, the core structural parameters of the valve body are optimized in a coordinated manner to achieve a unity of multiphase flow adaptability, water hammer protection performance and structural strength. This solves the problems of poor water hammer protection effect, easy structural damage and insufficient adaptability of traditional valves under multiphase flow conditions.

[0006] To achieve the above objectives, this invention proposes a method for optimizing the structure of a water hammer protection valve body based on multiphase flow adaptation, comprising the following steps:

[0007] Step S1: Obtain the multiphase flow parameters of the pipeline system where the valve is located, and establish a multiphase flow medium flow model and a water hammer pressure calculation model;

[0008] Step S2: Coupled analysis of the influence of multiphase flow parameters on water hammer pressure to determine key indicators for water hammer protection;

[0009] Step S3: Select the valve body structural parameters as design variables, construct a three-dimensional model of the valve body, and determine the value range and constraints of each structural parameter;

[0010] Step S4: Establish a multi-objective optimization model based on key indicators of water hammer protection, and use an intelligent optimization algorithm to solve for the optimal combination of structural parameters; among which, the optimization objectives are to minimize the multiphase flow resistance coefficient, minimize the peak water hammer pressure, and minimize the maximum stress of the valve body;

[0011] Step S5: Based on multiphase flow numerical simulation and structural strength simulation, verify the optimal combination of structural parameters. If the design requirements are met, output the optimized design scheme; if not, return to step S3 to adjust the range of structural parameter values ​​or constraints, and repeat steps S3-S5 until the design requirements are met.

[0012] Preferably, in step S1, the multiphase flow operating parameters include the medium density. Gas phase volume fraction Solid particle size Average fluid velocity v Pipe diameter D, valve inlet and outlet pressure difference Δ P Fluid dynamic viscosity .

[0013] Preferably, the multiphase flow model adopts the Euler-Euler two-fluid model, considering the interphase slip effect. Its gas phase continuity equation, liquid phase continuity equation, gas phase momentum equation, and liquid phase momentum equation are as follows:

[0014] ;

[0015] ;

[0016] ;

[0017] ;

[0018] in, For gas phase density, The gas phase velocity vector, For time, The density of the liquid phase is... For liquid phase velocity vector, For pressure, For the gas-responsive force tensor, It is the acceleration due to gravity. This is the gas-liquid phase drag coefficient. Let the fluid force tensor be... For gradient operators;

[0019] gas-liquid phase drag coefficient The calculation formula is as follows:

[0020] ;

[0021] in, This is the drag coefficient. The equivalent diameter of the bubble is given.

[0022] Preferably, the water hammer pressure calculation model adopts the improved water hammer equation, as shown in the following formula:

[0023] ;

[0024] in, This represents the peak value of the water hammer pressure. For multiphase flow mixing density, The propagation velocity of pressure waves in multiphase flow. This represents the abrupt change in fluid velocity.

[0025] Pressure wave propagation velocity in multiphase flow The calculation formula is as follows:

[0026] ;

[0027] ;

[0028] in, For the bulk elastic modulus of multiphase flow mixing, This refers to the bulk modulus of elasticity in the gas phase. This is the bulk modulus of elasticity in the liquid phase.

[0029] Preferably, in step S2, the key indicators for water hammer protection include: the peak water hammer pressure is less than 80% of the valve's rated pressure-bearing capacity, and the multiphase flow resistance coefficient. ≤0.03, solid phase particle throughput ≥95%, gas phase discharge efficiency ≥98%.

[0030] Preferably, in step S3, the design variables include the valve seat inner diameter. d Valve core cone angle Flow channel curvature radiusR Buffer cavity diameter Length of buffer chamber L Valve seat sealing surface width b The design variable vector is ;

[0031] The constraints include structural interference constraints, strength constraints, and flow constraints; among them, the structural interference constraint is the minimum clearance between the valve core and the valve seat; the strength constraint is the maximum stress of the valve body; and the flow constraint is the flow velocity of the multiphase medium in the valve body.

[0032] Preferably, in step S4, the optimization objective is specifically designed as follows:

[0033] Minimize peak water hammer pressure ;

[0034] Minimize the multiphase flow resistance coefficient. The formula is as follows:

[0035] ;

[0036] in, The equivalent diameter of the flow channel inside the valve body. The equivalent length of the flow channel;

[0037] Minimize the maximum stress on the valve body. The formula is as follows:

[0038] ;

[0039] in, For water hammer impact force, This refers to the bending moment generated on the cross-section of the valve body under water hammer impact. This is the distance from the stress-bearing section of the valve body to the neutral axis of that section. The force-bearing area of ​​the valve body. Let be the moment of inertia of the valve body cross section.

[0040] Preferably, the multi-objective optimization model uses a weighted summation method to transform multiple objectives into a single objective, as shown in the following formula:

[0041] ;

[0042] in, , , These are the weighting coefficients. , These are the minimum and maximum values ​​of the multiphase flow resistance coefficient, respectively. To optimize the peak water hammer pressure, This is the minimum value among the peak values ​​of water hammer pressure. This represents the maximum value among the maximum stresses in the valve body. It is the minimum value of the maximum stress. To optimize the maximum value of the maximum stress on the valve body before optimization.

[0043] Preferably, the intelligent optimization algorithm is the NSGA-II algorithm, and the solution steps include:

[0044] Step S41: Randomly generate N design variable vectors as the initial population, where N takes the value of 100-200;

[0045] Step S42: For each individual in the population, calculate the corresponding... , and Substitute the values ​​into the objective function to calculate the fitness value;

[0046] Step S43: Perform non-dominated ranking on the individuals in the population, divide them into different non-dominated levels, and calculate the crowding degree of each individual;

[0047] Step S44: Select superior individuals using the roulette wheel selection method, with a crossover probability of 0.8-0.9 and a mutation probability of 0.01-0.05, to generate a new generation population;

[0048] Step S45: Repeat steps S42-S44 until the number of iterations reaches the preset value or the objective function value converges, and output the Pareto optimal solution set;

[0049] Step S46: From the Pareto optimal solution set, and in combination with the actual engineering requirements, select the design variable combination with the best overall performance.

[0050] Preferably, in step S5, the optimal combination of structural parameters is verified, as follows:

[0051] Step S51: Substitute the optimal structural parameters into the multiphase flow model, and use numerical simulation software to analyze the flow state, pressure distribution, gas phase discharge efficiency and solid phase particle throughput of the multiphase flow medium in the valve body to verify whether it meets the key indicators for water hammer protection.

[0052] Step S52: Substitute the optimal structural parameters into the three-dimensional model of the valve body, and use finite element analysis software to calculate the stress distribution and strain distribution of the valve body under water hammer impact, and verify whether the maximum stress meets the strength constraint conditions.

[0053] Step S53: If the simulation and modeling results meet the design requirements, output the optimized design scheme; if not, return to step S3 to adjust the range of design variable values ​​or constraints, and re-perform parametric modeling and optimization calculations.

[0054] Therefore, this invention proposes an optimized design method for the body structure of a water hammer protection valve based on multiphase flow adaptation, the benefits of which are as follows:

[0055] (1) This invention takes multiphase flow adaptation as its core, breaks through the limitations of traditional single-phase flow design, and makes the valve structure design fit the actual multiphase flow conditions by quantifying the correlation between multiphase flow conditions and water hammer characteristics. It effectively solves problems such as air resistance, blockage, and secondary water hammer under multiphase flow conditions, and improves the pertinence of water hammer protection.

[0056] (2) The present invention adopts a multi-objective collaborative optimization mode, which takes into account the adaptability of multiphase flow, water hammer protection performance and structural strength, avoids the performance imbalance caused by single objective optimization, and ensures that the valve has good structural stability while effectively protecting against water hammer, and adapts to the long-term operation requirements of complex multiphase flow pipeline systems.

[0057] (3) This invention combines parametric modeling and intelligent optimization algorithms to achieve precise optimization of valve structure parameters, reducing design blindness; and the optimization process is quantifiable and repeatable, equipped with quantitative calculation formulas, which can accurately guide engineering design and facilitate promotion and application, solving the pain points of poor adaptability and lack of quantitative basis of existing optimization methods.

[0058] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0059] Figure 1 This is a flowchart of the water hammer protection valve body structure optimization design method based on multiphase flow adaptation according to the present invention;

[0060] Figure 2 This is a schematic diagram illustrating the solution steps of the intelligent optimization algorithm NSGA-Ⅱ in this invention;

[0061] Figure 3 This is a schematic diagram of the process for verifying the optimal combination of structural parameters in this invention. Detailed Implementation

[0062] To make the technical solutions, advantages, and objectives of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below. The described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0063] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0064] Example 1

[0065] This case study focuses on an oil pipeline system in a petrochemical enterprise containing a gas-liquid two-phase flow. It presents an optimized design for a floor-mounted water hammer protection valve body structure. The pipeline has a nominal diameter D=200mm, a rated pressure of 1.6MPa, and the medium is a mixed multiphase flow of crude oil (liquid phase) and natural gas (gas phase). The site exhibits problems such as water hammer impact causing valve seal damage and gas phase accumulation inducing secondary water hammer. The optimization design was completed using the method of this invention.

[0066] Before the design optimization, the basic parameters of the oil pipeline system in this embodiment are as follows:

[0067] 1. Pipeline system parameters: Nominal diameter of oil pipeline D = 200mm (0.2m), pipeline length 1500m, medium transport capacity 50m³ / h 3 / h, normal operating pressure 0.8-1.2MPa, operating temperature 25℃;

[0068] 2. Multiphase flow operating parameters: Medium density ρ (crude oil) =850kg / m 3 ,natural gas =0.75kg / m 3 ), gas phase volume fraction =0.08 (dimensionless), solid particle size =0.05mm (impurities), average fluid velocity v =1.4m / s, valve inlet and outlet pressure difference Δ P =0.15MPa (150000Pa), fluid dynamic viscosity =0.001 Pa·s;

[0069] 3. Valve basic parameters: The existing valve is a traditional gate valve, with a valve seat inner diameter of... d =0.16m, valve core cone angle =30°, flow channel curvature radius R =0.08m, no buffer cavity structure, material is 304 stainless steel, allowable stress [ ] = 137 MPa (137 × 10 6 Pa);

[0070] 4. Existing problem: Peak water hammer pressure before optimization =2.2MPa (exceeding 80% of the rated pressure of 1.6MPa, i.e., 1.28MPa), multiphase flow resistance coefficient =0.042 (greater than 0.03), gas phase discharge efficiency 92% (less than 98%), solid phase particle throughput 93% (less than 95%), valve sealing surface is easily worn, service life less than 1 year.

[0071] like Figure 1 As shown, the specific optimization implementation steps are as follows:

[0072] Step S1: Obtain the multiphase flow parameters of the pipeline system where the valve is located, and establish a multiphase flow medium flow model and a water hammer pressure calculation model;

[0073] Step S11: Verify the above-mentioned multiphase flow operating parameters through on-site online monitoring instruments to ensure that the data is true and reliable, and to provide a basis for subsequent modeling and optimization;

[0074] Step S12: Using the Euler-Euler two-fluid model, considering the gas-liquid phase slip effect, and substituting the measured parameters, establish the gas-liquid phase continuity equation and momentum equation; wherein, the formula for calculating the gas-liquid phase drag coefficient is as follows:

[0075] ;

[0076] Take the drag coefficient =0.45, equivalent bubble diameter =0.1mm, calculated as follows =18.6kg / (m 3 ·s);

[0077] Step S13: Calculate the peak water hammer pressure before optimization using the improved water hammer equation;

[0078] Multiphase flow mixing density:

[0079] ;

[0080] Multiphase flow mixing bulk modulus:

[0081] ;

[0082] Pick =1.0×10 5 Pa, =1.5×10 9 Pa, calculated =1.38×10 9 Pa;

[0083] Pressure wave propagation velocity in multiphase flow The calculation formula is as follows:

[0084] ;

[0085] Fluid velocity abrupt change =0.8 m / s (actual velocity change during water hammer), the peak water hammer pressure before optimization was:

[0086] .

[0087] Step S2: Analyze the gas phase volume fraction using numerical simulation with Fluent software. Flow rate v The impact on peak water hammer pressure was investigated, and key indicators for water hammer protection were determined: peak water hammer pressure ≤ 1.28 MPa (1.6 MPa × 80%), and flow resistance coefficient. ≤0.03, solid phase particle throughput ≥95%, gas phase discharge efficiency ≥98%.

[0088] Step S3: Select the valve body structural parameters as design variables, construct a three-dimensional model of the valve body, and determine the value range and constraints of each structural parameter;

[0089] Step S31: Combining the valve structure and multiphase flow adaptation requirements of the case study, select 6 core design variables and design variable vector. The variables are defined as follows: valve seat inner diameter d ( m ), valve core cone angle (°), Flow channel curvature radius R ( m ), buffer cavity diameter ( m ), buffer chamber length L ( m ), valve seat sealing surface width b ( m );

[0090] Step S32: Determine the range of values ​​for the design variables and the constraints:

[0091] Value range: 0.8 D ≤ d ≤0.95 D (0.16m≤ d ≤0.19m), 30°≤ ≤60°, 0.5 d ≤ R ≤ d 1.2 d ≤ ≤1.5 d 0.8 ≤ L ≤1.2 0.01 d ≤ b ≤0.03 d ;

[0092] The constraints include: structural interference constraint: minimum clearance between valve core and valve seat ≥ 0.001m; strength constraint: maximum stress of valve body. ≤137MPa; Flow constraint: The flow velocity of the multiphase medium in the valve body is ≤10m / s;

[0093] Step S33: Using SolidWorks 2023 software, construct a three-dimensional model of the valve body based on the above design variables, value ranges and constraints, and realize the linkage between design variables and model geometric dimensions.

[0094] Step S4: Establish a multi-objective optimization model based on key indicators of water hammer protection, and use an intelligent optimization algorithm to solve for the optimal combination of structural parameters;

[0095] Step S41: Determine the optimization objective:

[0096] Minimize peak water hammer pressure The calculation method is the same as step S13;

[0097] Minimize the multiphase flow resistance coefficient. The formula is as follows:

[0098] ;

[0099] Among them, the equivalent diameter of the flow channel inside the valve body =0.18m, equivalent length of the flow channel =0.5m;

[0100] Minimize the maximum stress on the valve body. The formula is as follows:

[0101] ;

[0102] Among them, water hammer impact force = Bending moment generated in the cross section of the valve body under water hammer impact = The distance from the stress-bearing section of the valve body to the neutral axis of that section. =0.05m, Moment of inertia of valve body section =5.0×10 -6 m 4 .

[0103] Step S42: Use a weighted summation method to transform multiple objectives into a single objective. The weighting coefficients are set based on the severity of the case conditions. =0.35、 =0.4、 =0.25, the optimized model is:

[0104] ;

[0105] And it satisfies all the constraints in step S32.

[0106] Step S43, as Figure 2 As shown, the intelligent optimization algorithm is the NSGA-II algorithm, and the solution steps include:

[0107] Step S431: Initialize the population: Randomly generate 150 design variable vectors as the initial population (N=150).

[0108] Step S432, Fitness Calculation: For each individual in the population, fitness is calculated using Fluent multiphase flow numerical simulation. , Calculation using ANSYS finite element analysis Substitute the values ​​into the objective function to calculate the fitness value;

[0109] Step S433: Non-dominated ordination: Perform non-dominated ordination on 150 individuals in the population, divide them into 3 non-dominated levels, calculate the crowding degree of each individual, and ensure population diversity.

[0110] Step S434: Selection, crossover, and mutation operations: Use the roulette wheel selection method to select superior individuals, with a crossover probability of 0.85 and a mutation probability of 0.03 to generate a new generation population;

[0111] Step S435, Iteration Termination: Repeat steps S432-S434. After 100 iterations, the objective function value converges, and the Pareto optimal solution set is output.

[0112] Step S436, Optimal Parameter Selection: Based on the actual case project, the optimal combination of design variables with the best overall performance is selected from the Pareto optimal solution set. The final optimal parameters are as follows:

[0113] Valve seat inner diameter d =0.18m (0.9D), valve core cone angle =45°, flow channel curvature radius R =0.144m (0.8) d ), buffer cavity diameter =0.234m (1.3) d ), buffer chamber length L =0.234m (1.0 ), Valve seat sealing surface width b =0.0036m (0.02) d ).

[0114] Step S5, as follows Figure 3 As shown, the optimal combination of structural parameters is verified based on multiphase flow numerical simulation and structural strength simulation, as detailed below:

[0115] Step S51, Multiphase Flow Numerical Simulation Verification: Substitute the above optimal parameters into the multiphase flow model established in S12, and perform numerical simulation using Fluent software. The simulation results show: Flow resistance coefficient =0.024 (≤0.03), solid phase particle throughput 97.5% (≥95%), gas phase discharge efficiency 98.8% (≥98%), all of which meet the key indicators for water hammer protection;

[0116] Step S52, Structural strength simulation verification: Substitute the optimal parameters into the SolidWorks 3D model, import it into ANSYS software for finite element analysis, and calculate the maximum stress of the valve body. =112MPa (≤137MPa), meeting the strength constraint conditions; peak water hammer pressure. =1.15MPa (≤1.28MPa), significantly improving water hammer protection effect;

[0117] Step S53, Result Judgment and Adjustment: If both the simulation and modeling results meet the design requirements, there is no need to adjust the design variables. Output the optimized valve body structure design scheme, including the optimal parameter list, 3D model (.step format), machining drawings (CAD format), and installation instructions.

[0118] Based on the optimized parameters, 304 stainless steel material was used, and the valve was processed in strict accordance with the processing drawings. After processing, the dimensions were inspected, and the deviation of all structural parameters from the optimized values ​​was ≤ ±0.001m, which met the processing accuracy requirements.

[0119] The optimized valves were installed on the target oil pipeline system and put into trial operation for 3 months. During this period, the occurrence of water hammer, valve operation status and multiphase flow effect were monitored, as shown in Table 1.

[0120] Table 1 Comparison of effects with existing traditional valves

[0121]

[0122] As shown in Table 1, the optimized valve effectively solves the problems of insufficient water hammer protection, poor adaptability to multiphase flow, and easy valve damage on site, verifying the practicality and feasibility of the method of the present invention, and can be extended to the design of water hammer protection valves for similar multiphase flow pipeline systems.

[0123] It is worth noting that all contents not described in detail in this invention are existing technologies and are well known to those skilled in the art.

[0124] Therefore, this invention provides a method for optimizing the design of the valve body structure for water hammer protection based on multiphase flow adaptation. By combining multi-objective collaborative optimization, parametric modeling and intelligent optimization algorithms, it can not only specifically solve problems such as air resistance, blockage and secondary water hammer under multiphase flow conditions, but also achieve precise quantitative optimization of valve structure, improve water hammer protection effect and structural stability. Moreover, the method is quantifiable, easy to promote and adaptable to the long-term operation of complex pipeline systems.

[0125] Finally, it should be noted that 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 or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for optimizing the structural design of a water hammer protection valve body based on multiphase flow adaptation, characterized in that, Includes the following steps: Step S1: Obtain the multiphase flow parameters of the pipeline system where the valve is located, and establish a multiphase flow medium flow model and a water hammer pressure calculation model; Step S2: Coupled analysis of the influence of multiphase flow parameters on water hammer pressure to determine key indicators for water hammer protection; Step S3: Select the valve body structural parameters as design variables, construct a three-dimensional model of the valve body, and determine the value range and constraints of each structural parameter; Step S4: Establish a multi-objective optimization model based on key indicators of water hammer protection, and use an intelligent optimization algorithm to solve for the optimal combination of structural parameters; among which, the optimization objectives are to minimize the multiphase flow resistance coefficient, minimize the peak water hammer pressure, and minimize the maximum stress of the valve body; Step S5: Based on multiphase flow numerical simulation and structural strength simulation, verify the optimal combination of structural parameters. If the design requirements are met, output the optimized design scheme; if not, return to step S3 to adjust the range of structural parameter values ​​or constraints, and repeat steps S3-S5 until the design requirements are met. In step S1, the multiphase flow operating parameters include the medium density. Gas phase volume fraction Solid particle size Average fluid velocity v Pipe diameter D, valve inlet and outlet pressure difference Δ P Fluid dynamic viscosity ; The multiphase flow model adopts the Euler-Euler two-fluid model, considering the interphase slip effect. Its gas phase continuity equation, liquid phase continuity equation, gas phase momentum equation, and liquid phase momentum equation are as follows: ； ； ； ； in, For gas phase density, The gas phase velocity vector, For time, The density of the liquid phase is... For liquid phase velocity vector, For pressure, For the gas-responsive force tensor, It is the acceleration due to gravity. This is the gas-liquid phase drag coefficient. Let the fluid force tensor be... For gradient operators; gas-liquid phase drag coefficient The calculation formula is as follows: ； in, This is the drag coefficient. Equivalent diameter of the bubble; The water hammer pressure calculation model adopts the improved water hammer equation, as shown in the following formula: ； in, This represents the peak value of the water hammer pressure. For multiphase flow mixing density, The propagation velocity of pressure waves in multiphase flow. This represents the abrupt change in fluid velocity. Pressure wave propagation velocity in multiphase flow The calculation formula is as follows: ； ； in, For the bulk elastic modulus of multiphase flow mixing, This refers to the bulk modulus of elasticity in the gas phase. This is the bulk modulus of elasticity in the liquid phase.

2. The method for optimizing the structure of a water hammer protection valve body based on multiphase flow adaptation as described in claim 1, characterized in that, In step S2, the key indicators for water hammer protection include: peak water hammer pressure and multiphase flow resistance coefficient. Solid phase particle throughput and gas phase discharge efficiency.

3. The method for optimizing the structure of a water hammer protection valve body based on multiphase flow adaptation according to claim 2, characterized in that, In step S3, the design variables include the valve seat inner diameter. d Valve core cone angle Flow channel curvature radius R Buffer cavity diameter Length of buffer chamber L Valve seat sealing surface width b The design variable vector is ; The constraints include structural interference constraints, strength constraints, and flow constraints; among them, the structural interference constraint is the minimum clearance between the valve core and the valve seat; the strength constraint is the maximum stress of the valve body; and the flow constraint is the flow velocity of the multiphase medium in the valve body.

4. The method for optimizing the structure of a water hammer protection valve body based on multiphase flow adaptation according to claim 3, characterized in that, In step S4, the optimization objective is specifically designed as follows: Minimize peak water hammer pressure ; Minimize the multiphase flow resistance coefficient. The formula is as follows: ； in, The equivalent diameter of the flow channel inside the valve body. The equivalent length of the flow channel; Minimize the maximum stress on the valve body. The formula is as follows: ； in, For water hammer impact force, This refers to the bending moment generated on the cross-section of the valve body under water hammer impact. This is the distance from the stress-bearing section of the valve body to the neutral axis of that section. The force-bearing area of ​​the valve body. Let be the moment of inertia of the valve body cross section.

5. The method for optimizing the structure of a water hammer protection valve body based on multiphase flow adaptation according to claim 4, characterized in that, The multi-objective optimization model uses a weighted summation method to transform multiple objectives into a single objective, as shown in the following formula: ； in, , , These are the weighting coefficients. , These are the minimum and maximum values ​​of the multiphase flow resistance coefficient, respectively. To optimize the peak water hammer pressure, This is the minimum value among the peak values ​​of water hammer pressure. This represents the maximum value among the maximum stresses in the valve body. It is the minimum value of the maximum stress. To optimize the maximum value of the maximum stress on the valve body before optimization.

6. The method for optimizing the structure of a water hammer protection valve body based on multiphase flow adaptation according to claim 5, characterized in that, The intelligent optimization algorithm is the NSGA-II algorithm, and the solution steps include: Step S41: Randomly generate N design variable vectors as the initial population, where N takes the value of 100-200; Step S42: For each individual in the population, calculate the corresponding... , and Substitute the values ​​into the objective function to calculate the fitness value; Step S43: Perform non-dominated ranking on the individuals in the population, divide them into different non-dominated levels, and calculate the crowding degree of each individual; Step S44: Select superior individuals using the roulette wheel selection method, with a crossover probability of 0.8-0.9 and a mutation probability of 0.01-0.05, to generate a new generation population; Step S45: Repeat steps S42-S44 until the number of iterations reaches the preset value or the objective function value converges, and output the Pareto optimal solution set; Step S46: From the Pareto optimal solution set, and in combination with the actual engineering requirements, select the design variable combination with the best overall performance.

7. The method for optimizing the structure of a water hammer protection valve body based on multiphase flow adaptation according to claim 6, characterized in that, In step S5, the optimal combination of structural parameters is verified, as follows: Step S51: Substitute the optimal structural parameters into the multiphase flow model, and use numerical simulation software to analyze the flow state, pressure distribution, gas phase discharge efficiency and solid phase particle throughput of the multiphase flow medium in the valve body to verify whether it meets the key indicators for water hammer protection. Step S52: Substitute the optimal structural parameters into the three-dimensional model of the valve body, and use finite element analysis software to calculate the stress distribution and strain distribution of the valve body under water hammer impact, and verify whether the maximum stress meets the strength constraint conditions. Step S53: If the simulation and modeling results meet the design requirements, output the optimized design scheme; if not, return to step S3 to adjust the range of design variable values ​​or constraints, and re-perform parametric modeling and optimization calculations.

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