Corrosion wear measurement method for gas-liquid-solid three-phase flow pipelines in the presence of oxide layer

Abstract

The present invention discloses a method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer. The method comprises using modeling software to model and mesh the pipeline; secondly, loading a coupling interface for continuous phase and discrete phase calculations and selecting a corresponding multiphase flow model, turbulence model, and particle motion model to obtain particle and continuous phase motion information in the calculation domain. At the same time, parameters such as the corresponding turbulence dissipation rate must be input. Finally, the corrosion wear model is loaded during the simulation process to obtain the corrosion wear rate of the gas-liquid-solid three-phase flow pipeline, thereby quantitatively characterizing the degree of corrosion wear of the gas-liquid-solid three-phase flow pipeline. The present invention can predict high-risk areas for pipeline corrosion wear. By constructing a method for predicting corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer, it is of great significance for pipeline corrosion wear protection, ensuring safe production of oil and gas fields, and reducing economic losses.

Description

Technical Field

[0001] The invention belongs to the field of fluid machinery and industrial pipeline corrosion and wear failure, and particularly relates to a method for measuring corrosion and wear of a gas-liquid-solid three-phase flow pipeline under the condition of the existence of an oxide layer. Background Art

[0002] In petrochemical companies, pipelines are crucial transportation tools for industrial production. With the rapid growth of industrial demand, my country's petrochemical industry is experiencing rapid development of pipelines, with the scale and speed of pipeline construction ranking among the highest in the world. In recent years, accidents caused by pipeline corrosion and wear have become commonplace.

[0003] Corrosive wear is the combined effect of mechanical action and electrochemical corrosion caused by the rapid flow of unstable fluids and solids on metal surfaces. Corrosion is primarily a process in which electrochemical action causes material loss and destruction, while wear refers to the phenomenon in which solid particles impact the surface of a material at a certain speed and angle, causing material loss. The combined effect of these two processes is considered corrosive wear. Because wear and corrosion promote each other, the substrate loss caused by their synergistic effect is far greater than the sum of the losses caused by wear and corrosion alone, which has a significant impact on the stable operation of pipeline equipment. At the same time, the mixed flow process of gas-liquid-solid three-phase flow is a complex multiphase flow coupling dynamics problem. The relationship between particle parameters and the physical spatial scale of the flow channel directly affects the computational convergence, and its numerical modeling and mesh processing are highly difficult. Summary of the Invention

[0004] To address the problems presented in the prior art, the present invention provides a method for measuring corrosion wear in gas-liquid-solid three-phase flow pipelines in the presence of an oxide layer. Based on a fluid volume-discrete element coupling model, a three-phase dynamics model that considers particle motion is established. Bidirectional coupling between the two-phase fluid and particles is achieved by solving the momentum equation.

[0005] The technical solution adopted by the present invention comprises the following steps:

[0006] Step S1: First, based on the physical structure of the industrial pipeline, a three-dimensional model of the industrial pipeline is constructed using the fluid simulation software FLUENT in the processor, and the constructed three-dimensional model is meshed;

[0007] Step S2: Next, the meshed three-dimensional pipeline model is imported into the discrete element software EDEM of the processor, and particles are loaded into the discrete element software EDEM to obtain an initial particle field;

[0008] Step S3, loading a coupling interface between the fluid simulation software and the discrete element software into the processor, so that the particle field information in the discrete element software can be imported into the fluid simulation software via the coupling interface;

[0009] Step S4: setting calculation control parameters in the fluid simulation software, assigning material characteristic parameters to the three-dimensional model, and determining boundary conditions;

[0010] Step S5: Load the corrosion wear model in the discrete element software; define wear influencing parameters at the entrance of the pipeline three-dimensional model in the fluid simulation software, and then use the fluid simulation software to obtain gas-liquid two-phase flow field information in the calculation domain;

[0011] Step S6: The gas-liquid two-phase flow field information acquired in step S5 is transmitted back to the discrete element software via the coupling interface. The discrete element software then obtains the wall mass loss due to corrosion wear of the gas-liquid-solid three-phase flow pipeline based on the loaded corrosion wear model and the solid phase information after being affected by the gas-liquid two-phase flow field. The wall mass loss due to corrosion wear of the industrial pipeline under actual operating conditions is predicted based on this wall mass loss. The degree of corrosion wear of the gas-liquid-solid three-phase flow pipeline is quantitatively characterized by the wall mass loss due to corrosion wear.

[0012] In step S2, the specific method of obtaining the particle field in the discrete element software is:

[0013] First, a particle factory is set up at the entrance of a pipe in the 3D model. Material properties for the pipe and the particles within it, as well as contact parameters between the particles and the pipe, are set. The particle factory then loads the particles with these parameters. Next, a particle motion model is loaded into the discrete element software and used to define the particle motion state. The moving particles form a particle field within the 3D model. Contact parameters include the rolling friction coefficient, static friction coefficient, and restitution coefficient between the particles / pipe and the particles.

[0014] In the discrete element software, the particle motion model is expressed as follows:

[0015]

[0016] Among them, v i represents the linear velocity of the i-th particle loaded from the particle factory; ω i represents the angular velocity of the i-th particle; m i represents the mass of the i-th particle; t represents time; E c,ij represents the contact force between the i-th particle and the j-th particle; E lr,ij represents the non-contact force between the i-th particle and the j-th particle; F pf,i represents the interaction force between the i-th particle and the pipeline fluid; F g,i represents the volume force on the i-th particle; I i The moment of inertia of the i-th particle; M t,ijrepresents the contact torque between the i-th particle and the j-th particle; M r,i represents the contact torque between the ith particle and the pipe fluid.

[0017] In step S3, the particle motion trajectory function ε is set in the coupling interface between the fluid simulation software and the discrete element software. f :

[0018]

[0019] Among them, ε ps,n Represents the volume of particles within the nth grid into which the three-dimensional model is divided.

[0020] In the specific implementation, the discrete element software EDEM sets the motion state (angular velocity and linear velocity) of the particles through the particle motion model. After the particle field carries the motion state of the particles through the coupling interface, particles with motion state and motion trajectory can be obtained. The motion state and motion trajectory information of the particles can be transmitted to the fluid simulation software.

[0021] In step S4, the fluid simulation software includes the following settings: the solution method adopts the VOF simulation method, the turbulence model selects the k-εRNG turbulence model, the surface tension model selects the CSF surface tension model, and the multiphase flow model selects the VOF multiphase flow model; the turbulent kinetic energy and turbulent dissipation rate parameters are set, the boundary conditions adopt the velocity inlet boundary condition and the pressure outlet boundary condition, and the wall function adopts the no-slip wall function.

[0022] The expression of the CSF surface tension model loaded by the fluid simulation software in step S4 is as follows:

[0023]

[0024] Among them, F st is the surface tension; σ is the surface tension coefficient; n is the normal vector of the gas phase volume fraction; is the unit normal vector; u is the fluid velocity; α1 is the liquid phase volume fraction; α2 is the gas phase volume fraction; t represents the time parameter.

[0025] The expression of the turbulence model loaded by the fluid simulation software in step S4 is as follows:

[0026]

[0027] Where ρ1 is the liquid phase density; ρ2 is the gas phase density; μ1 is the liquid phase viscosity; μ2 is the gas phase viscosity; ρ is the density of the continuous phase; μ is the viscosity of the continuous phase; k is the turbulent kinetic energy; ε is the turbulent dissipation rate; G k is the term for turbulent kinetic energy generation due to the mean velocity gradient; G bY is the term for turbulent kinetic energy generated by buoyancy; M is the effect of compressible turbulent pulsating expansion on the total dissipation rate; S k and S ε is the Prandtl number corresponding to the turbulent kinetic energy and turbulent dissipation rate; C 1ε 、C 2ε and C 3ε are all empirical constants; x p 、x q is the coordinate of the particle in the computational domain, x p is the coordinate value of the particle on the p coordinate; x q The coordinate value of the particle on the q coordinate; u p is the velocity of the particle; σ k is the turbulent Prandtl number of the turbulent kinetic energy k; μ t is the turbulent viscosity; σ ε is the turbulent Prandtl number for the turbulent dissipation rate ε.

[0028] The expression of the corrosion wear model loaded by the discrete element software in step S5 is as follows:

[0029]

[0030] Among them, M t is the mass loss of the wall due to the impact of particles and the presence of a corrosive oxide film; k′ is a given constant related to the metal and its oxide; h is the thickness of the oxide layer of the corrosion product; ρ f is the oxide density; is the particle diameter; ρ p is the particle density; H s V is the corrosion base hardness; p is the particle impact velocity; α1 is the particle impact angle; e n is the particle recovery coefficient.

[0031] The interaction force F between the particles and the pipeline fluid in the particle motion model pf,i Including the fluid resistance F of the particles drag , the fluid resistance F of the particle drag According to the following formula:

[0032]

[0033] Among them, ε d Re represents the phase momentum exchange coefficient of particles; p Reynolds number of the particle; C d0 represents the resistance coefficient of the particle; b1, b2, b3, and b4 are all given constants related to the particle shape; Re is the Reynolds number of the fluid.

[0034] The wear influencing parameter set in step S5 is any one of the gas-liquid phase fraction, particle size, particle shape, and gas-liquid inlet velocity.

[0035] The gas-liquid phase fraction includes the gas phase fraction and the liquid phase fraction. The corrosion wear prediction method of the present invention is based on the following assumptions: during the collision between particles and particles and particles and walls, particles do not undergo plastic deformation or brittle fracture; and the electrostatic effect and adhesion effect during the particle impact process are ignored.

[0036] Using the DEM-VOF gas-liquid-solid three-phase flow coupling research method, combined with the EDEM API method to configure the corrosion environment, a numerical simulation study was conducted on the failure patterns of pipeline corrosion and wear coupling, realizing the prediction of high-risk areas of pipeline corrosion and wear. This method can study the influence of factors such as fluid medium velocity, particle concentration, particle diameter, gas-liquid phase fraction, and particle shape on the pipeline corrosion and wear coupling under these conditions, and obtain the fluid dynamics and corrosion and wear coupling parameters (multiphase velocity field, solid particle motion trajectory and distribution pattern, pipeline wall corrosion and wear rate).

[0037] The method of the present invention is based on VOF-DEM numerical simulation and corrosion wear model formula analysis to simulate the movement process of pipelines prone to corrosion wear under the operating conditions of gas-liquid-solid three-phase flow. The method takes into account the three-phase dynamic model of particle motion and realizes the bidirectional coupling of two-phase fluid and particles through the coupling interface of continuous phase calculation and discrete phase calculation. First, the pipeline is modeled and meshed using modeling software; secondly, the coupling interface is loaded and the corresponding multiphase flow model, turbulence model and particle motion model are selected to obtain the particle and continuous phase motion information in the calculation domain, and the corresponding turbulent dissipation rate and other parameters need to be input. Finally, the corrosion wear model is loaded during the calculation process and the distribution of corrosion wear areas on the pipe wall is obtained by weighted averaging, thereby determining the high-risk areas for corrosion wear in the pipeline.

[0038] The beneficial effects of the present invention are:

[0039] 1. The present invention uses computational fluid dynamics to predict the amount and distribution of corrosion wear on the wall of a gas-liquid-solid three-phase flow pipeline. Numerical analysis avoids a large number of tedious and difficult experimental investigations, saving experimental costs and time.

[0040] 2. The present invention analyzes the amount of corrosion wear and the distribution of corrosion wear on the pipeline through the bidirectional coupling of two-phase fluid and particles, and can more accurately and comprehensively predict the degree of corrosion wear damage in various areas of the pipeline wall.

[0041] 3. This invention uses computational fluid dynamics to predict the amount and distribution of corrosion wear on the pipeline wall, reducing the computational cost. It can also further shorten the computational cycle through subsequent algorithm optimization, thus providing assistance for the optimal design of the model.

[0042] 4. The present invention can observe more physical details during pipeline wear, such as the internal velocity field, gas-liquid-solid phase fraction field, etc., thereby providing technical ideas and theoretical support for further optimization design.

[0043] 5. The present invention can predict high-risk areas for pipeline corrosion and wear. By constructing a method for predicting corrosion and wear of gas-liquid-solid three-phase flow pipelines under the condition of the presence of an oxide layer, it is of great significance for protecting pipeline corrosion and wear, ensuring safe production in oil and gas fields, and reducing economic losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flowchart of an embodiment of the present invention.

[0045] Figure 2 This is a pipeline corrosion and wear diagram obtained by using the method of the present invention. DETAILED DESCRIPTION

[0046] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention. They are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. By referring to these contents, ordinary technicians in this field should be able to understand other possible implementation methods and the advantages of the present invention.

[0047] like Figure 1 As shown, according to the pipeline corrosion wear prediction method of two-phase fluid and particle bidirectional coupling according to an embodiment of the present invention, the specific embodiment process is as follows:

[0048] Step S1: First, based on the physical structure of the industrial pipeline, a three-dimensional model of the industrial pipeline is constructed using the fluid simulation software FLUENT in the processor, and the constructed three-dimensional model is meshed:

[0049] First, a 90° horizontal-vertical elbow pipe is 3D modeled and exported to IGS format. A mesh is then created based on the 3D pipe model, and the mesh is locally encrypted at the pipe wall. The mesh is then exported as a mesh file. The mesh file is then opened using the fluid simulation software FLUENT and exported as a Boundary Mesh file. The mesh size is generally set to 3-10 times the particle size to ensure calculation stability and accuracy.

[0050] Step S2: Next, the meshed pipeline three-dimensional model file Boundary Mesh is imported into the discrete element software EDEM of the processor, and particles are loaded into the discrete element software EDEM to obtain an initial particle field;

[0051] In step S2, the specific method of obtaining the particle field in the discrete element software is as follows:

[0052] First, a particle factory is set up at the entrance of a pipe in the 3D model. Material properties for the pipe and the particles within it, as well as contact parameters between the particles and the pipe, are set. The particle factory then loads the particles with these parameters. Next, a particle motion model is loaded into the discrete element software and used to define the particle motion state. The moving particles form a particle field within the 3D model. Contact parameters include the rolling friction coefficient, static friction coefficient, and restitution coefficient between the particles / pipe and the particles.

[0053] In the discrete element software implemented specifically, the expression of the particle motion model is as follows:

[0054]

[0055] Among them, v i represents the linear velocity of the i-th particle loaded from the particle factory; ω i represents the angular velocity of the i-th particle; m i represents the mass of the i-th particle; t represents time; F c,ij represents the contact force between the i-th particle and the j-th particle; F lr,ij represents the non-contact force between the i-th particle and the j-th particle; F pf,i represents the interaction force between the i-th particle and the pipeline fluid; F g,i represents the volume force on the i-th particle; I i The moment of inertia of the i-th particle; M t,ij represents the contact torque between the i-th particle and the j-th particle; M r,i represents the contact torque between the ith particle and the pipe fluid.

[0056] The interaction force F between particles and pipe fluid in the particle motion model pf,i Including the fluid resistance F of the particles drag , the fluid resistance F of the particle drag According to the following formula:

[0057]

[0058] Among them, ε dRe represents the interphase momentum exchange coefficient of the particles; Re represents the Reynolds number of the fluid; C d0 represents the resistance coefficient of the particle; b1, b2, b3, and b4 are all given constants related to the particle shape; Re is the Reynolds number of the fluid.

[0059] Among them, F pf,i =F drag +FG, FG represents the preset compensation interaction force.

[0060] Step S3: loading a coupling interface between the fluid simulation software and the discrete element software in the fluid simulation software, so that the particle field information in the discrete element software can be imported into the fluid simulation software via the coupling interface;

[0061] In step S3, the particle motion trajectory function ε is set in the coupling interface between the fluid simulation software and the discrete element software. f :

[0062]

[0063] Among them, ε ps,n Represents the volume of particles within the nth grid into which the three-dimensional model is divided.

[0064] In the specific implementation, the discrete element software EDEM sets the motion state (angular velocity and linear velocity) of the particles through the particle motion model. After the particle field carries the motion state of the particles through the coupling interface, particles with motion state and motion trajectory can be obtained. The motion state and motion trajectory information of the particles can be transmitted to the fluid simulation software.

[0065] Step S4: setting calculation control parameters in the fluid simulation software, assigning material characteristic parameters to the three-dimensional model, and determining boundary conditions;

[0066] In step S4, the fluid simulation software includes the following settings: the solution method adopts the VOF simulation method, the turbulence model selects the k-εRNG turbulence model, the surface tension model selects the CSF surface tension model, and the multiphase flow model selects the VOF multiphase flow model; the turbulent kinetic energy and turbulent dissipation rate parameters are set, the boundary conditions adopt the velocity inlet boundary condition and the pressure outlet boundary condition, and the wall function adopts the no-slip wall function.

[0067] The expression of the CSF surface tension model loaded by the fluid simulation software is as follows:

[0068]

[0069] Among them, F st is the surface tension; σ is the surface tension coefficient; n is the normal vector of the gas phase volume fraction; is the unit normal vector; u is the fluid velocity; α1 is the liquid phase volume fraction; α2 is the gas phase volume fraction; t represents the time parameter.

[0070] The expression of the turbulence model loaded by the fluid simulation software is as follows:

[0071]

[0072] Where ρ1 is the liquid phase density; ρ2 is the gas phase density; μ1 is the liquid phase viscosity; μ2 is the gas phase viscosity; ρ is the density of the continuous phase; μ is the viscosity of the continuous phase; k is the turbulent kinetic energy; ε is the turbulent dissipation rate; G k is the term for turbulent kinetic energy generation due to the mean velocity gradient; G b Y is the term for turbulent kinetic energy generated by buoyancy; M is the effect of compressible turbulent pulsating expansion on the total dissipation rate; S k and S ε is the Prandtl number corresponding to the turbulent kinetic energy and turbulent dissipation rate; C 1ε 、C 2ε and C 3ε are all empirical constants; x p 、x q is the coordinate of the particle in the computational domain, x p is the coordinate value of the particle on the p coordinate; x q The coordinate value of the particle on the q coordinate; u p is the velocity of the particle; σ k is the turbulent Prandtl number of the turbulent kinetic energy k; μ t is the turbulent viscosity; σ ε is the turbulent Prandtl number for the turbulent dissipation rate ε.

[0073] Step S5: Based on the particle field obtained in step S2, a corrosion wear model is loaded into the discrete element software; wear influencing parameters are defined at the entrance of the three-dimensional pipeline model of the fluid simulation software, and then the fluid simulation software is used to obtain the motion information of the gas-liquid two-phase in the calculation domain;

[0074] Among them, the expression of the corrosion wear model is as follows:

[0075]

[0076] Among them, M t is the mass loss of the wall due to the impact of particles and the presence of a corrosive oxide film; k′ is a given constant related to the metal and its oxide; h is the thickness of the oxide layer of the corrosion product; ρ f is the oxide density; is the particle diameter; ρ p is the particle density; H s V is the corrosion base hardness; pis the particle impact velocity; α1 is the particle impact angle; e n is the particle recovery coefficient.

[0077] Step S6: The gas-liquid two-phase flow information obtained in step S5 is transmitted back to the discrete element software via the coupling interface. The discrete element software obtains the corrosion wear wall mass loss (unit: g) of the gas-liquid-solid three-phase flow pipeline based on the loaded corrosion wear model and the solid phase motion information under the influence of the gas-liquid two-phase flow field. The corrosion wear wall mass loss is shown in the figure below: Figure 2 As shown in FIG, the wall mass loss due to corrosion wear of industrial pipelines under actual working conditions is obtained based on the wall mass loss due to corrosion wear. The degree of corrosion wear of gas-liquid-solid three-phase flow pipelines can be quantitatively characterized by the wall mass loss due to corrosion wear.

[0078] In summary, with the help of the above technical solutions of the present invention, the present invention quantitatively performs a bidirectional coupled corrosion and wear analysis of the fluid phase and the solid phase on the model based on the fluid volume-discrete element method. Through numerical analysis, a large number of tedious and difficult experimental explorations are avoided, and experimental costs and time are saved. At the same time, it can more accurately and comprehensively predict the degree of corrosion and wear damage in various areas of the model surface; by further shortening the calculation cycle through later algorithm optimization, it provides assistance for the optimization design of the model; the present invention can observe more physical details in the process of corrosion and wear of gas-liquid-solid three-phase flow, such as the internal pressure field, temperature field, etc., thereby providing technical ideas and theoretical support for further optimization design. By quantitatively analyzing the corrosion and wear of the model through the fluid volume-discrete element method, the degree of corrosion and wear damage in various areas of the model surface can be more accurately and comprehensively predicted.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer, characterized in that: The following steps are involved: Step S1: First, based on the physical structure of the industrial pipeline, a three-dimensional model of the industrial pipeline is constructed using the fluid simulation software FLUENT in the processor, and the constructed three-dimensional model is meshed; Step S2: Next, the meshed three-dimensional pipeline model is imported into the discrete element software EDEM of the processor, and particles are loaded into the discrete element software EDEM to obtain an initial particle field; Step S3, loading a coupling interface between the fluid simulation software and the discrete element software into the processor, so that the particle field information in the discrete element software is imported into the fluid simulation software via the coupling interface; Step S4: setting calculation control parameters in the fluid simulation software, assigning material characteristic parameters to the three-dimensional model, and determining boundary conditions; Step S5: Loading the corrosion wear model into the discrete element software of the processor; defining wear influencing parameters at the entrance of the pipeline three-dimensional model of the fluid simulation software; and then using the fluid simulation software to obtain gas-liquid two-phase flow field information in the calculation domain; Step S6: The gas-liquid two-phase flow field information obtained in step S5 is transmitted back to the discrete element software via the coupling interface. The discrete element software obtains the corrosion wear wall mass loss of the gas-liquid-solid three-phase flow pipeline based on the loaded corrosion wear model and the solid phase information after being affected by the gas-liquid two-phase flow field. The corrosion wear wall mass loss of the industrial pipeline under actual working conditions is obtained based on the corrosion wear wall mass loss. The expression of the corrosion wear model loaded by the discrete element software in step S5 is as follows: Among them, M t is the mass loss of the wall surface due to the impact of particles and the presence of a corrosive oxide film; k′ is a constant related to the metal and its oxide; h is the thickness of the oxide layer of the corrosion product; ρ f is the oxide density; is the particle diameter; ρ p is the particle density; H s V is the corrosion base hardness; p is the particle impact velocity; α1 is the particle impact angle; e n is the particle recovery coefficient.

2. The method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer according to claim 1, characterized in that: In step S2, the specific method of obtaining the particle field in the discrete element software is: First, a particle factory is set up at the pipeline entrance of the 3D model. The material property parameters of the pipeline and the particles in the pipeline, the contact parameters between the particles, and the contact parameters between the particles and the pipeline are set. Then, the particles with the set parameters are loaded using the particle factory. Next, the particle motion model is loaded into the discrete element software. The motion state of the particles is set through the particle motion model, and the moving particles form a particle field in the 3D model.

3. The method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer according to claim 2, characterized in that: In the discrete element software, the particle motion model is expressed as follows: Among them, v i represents the linear velocity of the i-th particle loaded from the particle factory; ω i represents the angular velocity of the i-th particle; m i represents the mass of the i-th particle; t represents time; F c,ij represents the contact force between the i-th particle and the j-th particle; F lr,ij represents the non-contact force between the i-th particle and the j-th particle; F pf，i represents the interaction force between the i-th particle and the pipeline fluid; F g，i represents the volume force on the i-th particle; I i The moment of inertia of the i-th particle; M t，ij represents the contact torque between the i-th particle and the j-th particle; M r,i represents the contact torque between the ith particle and the pipe fluid.

4. The method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer according to claim 1, characterized in that: In step S3, the particle motion trajectory function ε is set in the coupling interface between the fluid simulation software and the discrete element software. f : Among them, ε ps,n Represents the volume of particles within the nth grid into which the three-dimensional model is divided.

5. The method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer according to claim 1, characterized in that: In step S4, the fluid simulation software includes the following settings: the solution method adopts the VOF simulation method, the turbulence model selects the k-εRNG turbulence model, the surface tension model selects the CSF surface tension model, and the multiphase flow model selects the VOF multiphase flow model; the turbulent kinetic energy and turbulent dissipation rate parameters are set, the boundary conditions adopt the velocity inlet boundary condition and the pressure outlet boundary condition, and the wall function adopts the no-slip wall function.

6. The method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer according to claim 5, characterized in that: The expression of the CSF surface tension model loaded by the fluid simulation software in step S4 is as follows: Among them, F st is the surface tension; σ is the surface tension coefficient; n is the normal vector of the gas phase volume fraction; is the unit normal vector; u is the fluid velocity; α1 is the liquid phase volume fraction; α2 is the gas phase volume fraction; t represents the time parameter.

7. The method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer according to claim 5, characterized in that: The expression of the turbulence model loaded by the fluid simulation software in step S4 is as follows: Where ρ1 is the liquid phase density; ρ2 is the gas phase density; μ1 is the liquid phase viscosity; μ2 is the gas phase viscosity; ρ is the density of the continuous phase; μ is the viscosity of the continuous phase; k is the turbulent kinetic energy; ε is the turbulent dissipation rate; G k is the term for turbulent kinetic energy generation due to the mean velocity gradient; G b Y is the term for turbulent kinetic energy generated by buoyancy; M is the effect of compressible turbulent pulsating expansion on the total dissipation rate; S k and S ε is the Prandtl number corresponding to the turbulent kinetic energy and turbulent dissipation rate; C 1ε 、C 2ε and C 3ε are all empirical constants; x p 、x q is the coordinate of the particle in the computational domain; u p is the velocity of the particle; σ k is the turbulent Prandtl number of the turbulent kinetic energy k; μ t is the turbulent viscosity; σ ε is the turbulent Prandtl number for the turbulent dissipation rate ε.

8. The method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer according to claim 3, characterized in that: The interaction force F between the particles and the pipeline fluid in the particle motion model pf，i Including the fluid resistance F of the particles drag , the fluid resistance F of the particle drag According to the following formula: Among them, ε d Re represents the phase momentum exchange coefficient of particles; p Reynolds number of the particle; C d0 represents the drag coefficient of the particle; b1, b2, b3, and b4 are preset constants related to the particle shape; Re is the Reynolds number of the fluid.

9. The method for measuring corrosion wear of a gas-liquid-solid three-phase flow pipeline in the presence of an oxide layer according to claim 3, characterized in that: The wear influencing parameter set in step S5 is any one of the gas-liquid phase fraction, particle size, particle shape, and gas-liquid inlet velocity.

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