A method for analyzing local scour landforms of underwater pipelines

Abstract

The present invention discloses a method for analyzing local scour landforms in underwater pipelines. The method comprises: obtaining local sand bed parameters and flow field parameters of the underwater pipeline to be tested and constructing a model to obtain a discrete element model and a computational fluid dynamics model; setting boundary conditions for the discrete element model and the computational fluid dynamics model; and conducting numerical simulation experiments based on the boundary conditions and coupling the discrete element model and the computational fluid dynamics model to obtain simulated scour landform results. The present invention can address the problem that existing scour analysis methods are highly empirical and cannot reflect the actual movement of particles. As a method for analyzing local scour landforms in underwater pipelines, the present invention can be widely applied in the field of coastal dynamics technology.

Description

Technical Field

[0001] The present invention relates to the technical field of coastal dynamics, and in particular to a method for analyzing local scour landforms of underwater pipelines. Background Art

[0002] Pipeline transportation is the most direct and efficient way to transport all types of liquid and gaseous resources. Pipelines are the "lifeline" equipment in resource transportation. However, during operation, pipelines are easily eroded by water flow, resulting in exposure and suspension, shortening the pipeline's operating life and even causing serious accidents. During pipeline operation, the upstream water flow continuously scours the sand bed below the pipeline. The water flow drives several individual particles on the surface of the particle accumulation body around the pipeline, causing them to move at a speed along the flow direction, carrying them away from the sand bed, causing scour pits to form under the pipeline, and forming particle accumulation dunes downstream of the pipeline, ultimately forming scour landforms.

[0003] The traditional pipeline scour simulation method is based on a single-phase simulation method and uses a sediment transport model as a boundary condition. It is highly empirical and cannot simulate the motion state of particles and the motion state of water flow in the particles during the scour process, and has certain limitations. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a method for analyzing local scour landforms in underwater pipelines, which can solve the problem that existing scour analysis methods are highly empirical and cannot reflect the actual movement of particles.

[0005] To solve the above problems, the present invention provides a method for analyzing local scour landforms of underwater pipelines, comprising the following steps:

[0006] Obtain the local sand bed parameters and flow field parameters of the underwater pipeline to be tested and construct a model to obtain a discrete element model and a computational fluid dynamics model;

[0007] Set boundary conditions for discrete element models and computational fluid dynamics models;

[0008] Numerical simulation experiments were carried out based on the boundary condition coupling discrete element model and computational fluid dynamics model to obtain the simulated scour landform results.

[0009] Furthermore, the sand bed parameters include particle size gradation, particle accumulation friction angle and particle material density; the flow field parameters include upstream flow velocity, friction flow velocity, velocity zero point, wave period, wave height and wave velocity.

[0010] Furthermore, it also includes conducting physical parameter experiments on the particle accumulation body in the sand bed parameters to obtain the particle size, density and internal friction angle of the particles.

[0011] Furthermore, the boundary conditions of the discrete element model include:

[0012] If the water flow rate is less than the preset threshold, it is set as a fixed boundary condition;

[0013] If the water flow velocity is greater than a preset threshold, a periodic boundary condition is set in the water flow direction, and fixed boundary conditions are set in other directions.

[0014] Furthermore, the boundary conditions of the computational fluid dynamics model include: excluding the position of the particle discrete element model, the remaining sand bed positions are set as no-slip wall boundary conditions, the top of the flow field is set as a symmetric boundary condition, the inlet is set as a velocity inlet boundary condition, and the outlet is set as a pressure outlet boundary condition.

[0015] Furthermore, the inlet flow velocity uses a logarithmic flow distribution, and its calculation equation is as follows:

[0016]

[0017] In the above formula, u f is the frictional velocity, and z0 is the velocity zero point.

[0018] Furthermore, the step of conducting a numerical simulation experiment based on boundary condition coupling of a discrete element model and a computational fluid dynamics model to obtain a simulated scour landform result specifically includes:

[0019] Obtain the geometric dimensions of the space around the underwater pipeline to be tested and use the finite volume method to discretize the flow field to construct the computational fluid dynamics calculation grid;

[0020] Obtain the flow field state and input it into the discrete element model for calculation to obtain the particle state;

[0021] The particle state is input into the computational fluid dynamics model for calculation, the flow field state is calculated based on the proportion of particles in the finite volume method grid, and the results are updated;

[0022] The updated results are input into the discrete element model for repeated iteration until the calculation is stopped at the set time to obtain the scour landform results.

[0023] Furthermore, it also includes coupling calculation to perform two-dimensional simulation when the direction of the underwater pipeline to be tested is perpendicular to the direction of water flow.

[0024] Furthermore, during the coupling calculation process, the discrete element model calculation times are greater than those of the computational fluid dynamics model.

[0025] Furthermore, the Courant number of the computational fluid dynamics model is set to be less than 1.

[0026] The method of the present invention has the following beneficial effects: it fully utilizes the advantages of computational fluid dynamics and discrete element methods. By constructing a computational fluid dynamics model of the flow field around an underwater pipeline and a discrete element model of a sand bed particle accumulation, it simulates local scour around the pipeline. The simulation results accurately reflect the motion state of each particle during the scour process, fully reflect the flow field state in the sand bed, and ultimately calculate the scour landform around the pipeline when scour is balanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flowchart of the steps of a method for analyzing local scour landforms of underwater pipelines according to the present invention;

[0028] Figure 2 The flow field state and particle parameters around the underwater pipeline to be measured in a specific embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of grid division of the computational domain of the computational fluid dynamics model according to a specific embodiment of the present invention;

[0030] Figure 4 This is a schematic diagram of the particle position initialization process according to a specific embodiment of the present invention;

[0031] Figure 5 This is a schematic diagram of the boundary conditions of the discrete element model according to a specific embodiment of the present invention;

[0032] Figure 6 It is a schematic diagram of the erosion landform simulation results of a specific embodiment of the present invention. DETAILED DESCRIPTION

[0033] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The step numbers in the following embodiments are provided for ease of description only and do not limit the order of the steps. The order of execution of the steps in the embodiments can be adaptively adjusted based on the understanding of those skilled in the art.

[0034] Reference Figure 1 The present invention provides a method for analyzing local scour landforms of underwater pipelines, the method comprising the following steps:

[0035] S1. Obtain the local sand bed parameters and flow field parameters of the underwater pipeline to be tested and construct a model to obtain a discrete element model and a computational fluid dynamics model;

[0036] Specifically, the sand bed parameters include particle size distribution, particle accumulation friction angle and particle material density; the flow field parameters include upstream flow velocity, friction flow velocity, velocity zero point, wave period, wave height and wave velocity.

[0037] The discrete element model refers to a particle discrete element method contact model. The essence of the contact model is the elastic-plastic analysis of the contact mechanics of solid particles under pseudo-static conditions. The wet particle contact model is based on the presence of a liquid bridge between two spheres or an immersed state. When the two spheres are in normal-tangential relative motion, the normal extrusion force or tangential resistance generated by the fluid viscosity is considered. Therefore, the preferred discrete element model in this embodiment is the soft sphere model, and the Hertz-Mindlin model is used to calculate the contact normal and tangential forces between the particles.

[0038] Computational fluid dynamics (CFD) is a discipline that uses numerical methods to solve the governing equations of fluid dynamics to obtain a discrete quantitative description of the flow field, thereby predicting the laws of fluid motion. CFD equations can be divided into two categories: inviscid (Euler equations) and viscous (NS equations). Since the CFD of this embodiment is applied to the simulation of local scour landforms in a single pipeline on a flat sand bed under steady-state flow, and is primarily applicable to low-speed, incompressible flow phenomena, the preferred CFD model for this embodiment is the Reynolds time-averaged method to solve the NS equations, and the SST k-ω two-equation model is used as the turbulence model.

[0039] A granular deposit is a structure formed by the accumulation of a large number of particles. The granular deposit properties refer to the arrangement of particles within the particle body, the arrangement of particles in space, or the structural characteristics of the particle body.

[0040] Sand particle gradation refers to the proportion of sand particles of different sizes. A good gradation means that the gaps between coarse particles are exactly filled by medium particles, and the gaps between medium particles are exactly filled by fine particles. This gradual filling process creates the most compact sand packing, minimizing the void ratio and maximizing the packing density.

[0041] The basic equations used in the soft ball model are the momentum equation and the angular momentum equation. In the soft ball model, when two particles collide, it is assumed that the particles maintain their shape but are superimposed on each other. The greater the superimposed force, the greater the force exerted on the particles.

[0042] The Reynolds-time-averaged NS equations govern the average variables of the flow field. The associated simulation theory is known as turbulence pattern theory. Turbulence pattern theory assumes that the flow field variables in turbulent flow consist of a time-averaged quantity and a fluctuating quantity. By treating the NS equations from this perspective, the Reynolds-time-averaged NS equations can be derived. Furthermore, by introducing the Boussinesq hypothesis, which assumes that the turbulent Reynolds stress is proportional to the strain, turbulence calculations are reduced to calculating the proportionality coefficient between the Reynolds stress and strain (i.e., the turbulent viscosity coefficient). The model concept is that the statistical averaging of the governing equations eliminates the need to calculate turbulent fluctuations at various scales, requiring only the average motion. This reduces spatial and temporal resolution and computational workload. The three k-ε models used in computational fluid dynamics, the Spalart-Allmaras model, the k-ω model, and the Reynolds stress model all fall under turbulence pattern theory. The SST k-ω model was developed by Menter to be independent of the k-ε model in a wide range of fields, making the k-ω model widely applicable and accurate in near-wall free flow. To achieve this, the k-ε model was transformed into a k-ω formulation. The SST k-ω model is similar to the standard k-ω model, but with the following improvements: The SST k-ω model and the k-ε model are modified by blending functionality and the dual model is combined. The blending functionality is designed for the near-wall region, where the standard k-ω model is valid, and for the free surface, where the k-ε model is modified. The SST k-ω model incorporates cross-diffusion from the ω equations. The turbulent viscosity accounts for the propagation of turbulent shear stresses. The model constants are different. These improvements make the SST k-ω model more accurate and reliable than the standard k-ω model for a wide range of flow domains.

[0043] Furthermore, it is necessary to conduct physical parameter experiments on the particle accumulation in the sand bed parameters to obtain the particle size, density and internal friction angle of the particles.

[0044] Among them, the particle size adopts the median particle size, the density adopts the density of the particle material, and the particle internal friction angle adopts the tangent value of the particle accumulation friction angle. Based on this, the particle properties are set as follows: Figure 2 shown.

[0045] It should be noted that particle size is called particle size, while particle diameter is called particle diameter. Particle size is typically expressed in terms of diameter. As we know, only spherical geometric objects have diameters, but the shapes of materials actually measured vary, so a true diameter does not exist. Therefore, the particle size referred to in particle size distribution measurements is not the actual diameter of the particle, but rather a virtual "equivalent diameter." When a physical property of the measured particle most closely resembles that of a homogeneous sphere of a certain diameter, the diameter of that sphere is used as the equivalent diameter of the measured particle. Therefore, data from particle size measurement methods designed using different principles often differ significantly. While some instruments include software for conversion, this conversion is neither necessary nor accurate in practice. The median particle size refers to the particle size at which the cumulative particle size distribution percentage of a sample reaches 50%. Its physical meaning is that 50% of the particles have a diameter larger than this, and 50% of the particles have a diameter smaller than this.

[0046] S2. Setting boundary conditions of discrete element model and computational fluid dynamics model;

[0047] Specifically, the boundary conditions of the discrete element model are as follows: Figure 5 As shown:

[0048] If the water flow rate is less than the preset threshold, the water flow rate will cause clear water flushing, which is set as a fixed boundary condition;

[0049] It is determined that the water flow velocity is greater than the preset threshold. At this time, the large water flow velocity will cause moving bed scouring. A periodic boundary condition is set in the water flow direction, and fixed boundary conditions are set in other directions.

[0050] It should be noted that under fixed boundary conditions, particles will not pass through the wall, while under periodic boundary conditions, particles should appear from the opposite surface at the same speed after crossing the boundary.

[0051] The boundary conditions of the computational fluid dynamics model are as follows: Figure 3 As shown:

[0052] Except for the position of the particle discrete element model, the remaining sand bed positions are set as no-slip wall boundary conditions, the top of the flow field is set as a symmetric boundary condition, the inlet is set as a velocity inlet boundary condition, and the outlet is set as a pressure outlet boundary condition.

[0053] The inlet flow velocity uses a logarithmic flow distribution, and its calculation equation is as follows:

[0054]

[0055] In the above formula, u f is the frictional velocity, and z0 is the velocity zero point.

[0056] In this embodiment, if Figure 2As shown, the inlet flow velocity of the computational domain is set based on the incoming flow field state, u f =0.072, κ=0.04, z0=8.5×10 -5 .

[0057] S3. Numerical simulation experiments were conducted based on the boundary condition coupling discrete element model and computational fluid dynamics model to obtain the simulated scour landform results.

[0058] S3.1. Obtain the spatial geometric state around the underwater pipeline to be tested and determine the spatial position of the particle accumulation body. Initialize the spatial position of the particle accumulation body using the falling sand method.

[0059] Specifically, the detailed steps for initializing the spatial position of the particle accumulation body are as follows:

[0060] like Figure 4 As shown in the figure, when initializing the particle position, the particle accumulation body is densely spread on the water bottom by the falling sand method. When the particles are initially set, the bottom position is at the bottom of the study area, and the top is 1.5 times the height of the initial position of the particle. A certain length of time is simulated without the action of water flow. The specific initialization simulation time can be obtained by repeated simulations. It is only necessary to ensure that the particles have no obvious movement at the beginning of the coupling calculation.

[0061] S3.2. Obtain the geometric dimensions of the space surrounding the underwater pipeline to be measured and discretize the flow field using the finite volume method to construct a computational fluid dynamics grid;

[0062] like Figure 3 As shown, in this embodiment, the flow field domain in computational fluid dynamics is the physical domain, referring to the physical space containing the fluid to be studied. Specifically, it determines the geometric dimensions of the space surrounding the underwater pipeline under test. The computational domain is a fictitious regular space corresponding to this physical domain. For example, a two-dimensional problem corresponds to a fictitious rectangular plane, and a three-dimensional problem corresponds to a fictitious cube. While the grids in the physical domain vary in size, the grids in the computational domain are uniformly spaced in all directions.

[0063] It should be noted that the flow field in this embodiment includes the spatial geometric position of the discrete particle accumulation body.

[0064] The finite volume method (FVM) is a commonly used numerical algorithm in computational fluid dynamics. It is based on integral conservation equations, rather than differential equations, that describe each control volume defined by the computational grid. The FVM emphasizes constructing discrete equations from a physical perspective. Each discrete equation represents the conservation of a physical quantity over a finite volume. The derivation is based on clear physical concepts, and the coefficients of the discrete equations have physical meaning, ensuring that the discrete equations exhibit conservation properties.

[0065] S3.3, obtain the flow field state and input it into the discrete element model for calculation to obtain the particle state;

[0066] Specifically, the flow field state includes the pressure and flow velocity of the flow field, and the particle state includes the particle displacement, velocity and acceleration.

[0067] In the calculation process of the discrete element model, the density of the particle material and the particle size are first obtained to determine the calculation step size. Then, all the particles in the flow field are scanned every time step to calculate the resultant force, velocity, angular velocity and position of each particle. When the particles are in contact, the normal superposition and tangential superposition of a particle are first calculated, and then the magnitude of the resultant force is calculated. The impulse equation is used to calculate the velocity and position of the particle after one time step; then, based on the tangential force on the particle, the angular velocity of the particle after one time step is calculated using the angular momentum equation. In this way, the motion and force conditions of all particles in the flow field can be calculated within one time step, and thus the motion trajectory of all particles over a period of time can be calculated.

[0068] S3.4. Input the particle state into the computational fluid dynamics model for calculation, calculate the flow field state based on the proportion of particles in the finite volume method grid, and update the result;

[0069] Specifically, the Courant number should be as small as possible during the calculation of the computational fluid dynamics model. If it is larger than 1 and shows an obvious upward trend, the result should be invalidated and the calculation step should be adjusted and restarted.

[0070] S3.5. Input the updated results into the discrete element model and repeat the iteration until the calculation stops at the set time to obtain the scour landform results.

[0071] Specifically, repeated iteration refers to repeating steps S3.4 and S3.5, the discrete element model obtains the flow field state to calculate the flow field force on the particles, updates the displacement, velocity and acceleration state of the particles, and after several steps of calculation, the computational fluid dynamics model obtains the particle state, calculates the flow field state according to the proportion of the particles in the finite volume method grid and updates the result, and updates the data to the discrete element model for repeated iterative calculation. The calculation is stopped after two hours to obtain the scour landform result. The scour landform result of this embodiment is as follows: Figure 6 shown.

[0072] Among them, when the direction of the pipeline is perpendicular to the direction of water flow, the coupled calculation performs a two-dimensional simulation, that is, the water flow velocity, particle velocity and acceleration along the direction of the pipeline are not considered, and only the physical quantities perpendicular to the direction of the pipeline are calculated, thereby reducing the amount of calculation.

[0073] Furthermore, in order to improve the computational efficiency while ensuring the computational accuracy, the discrete element model is calculated more times than the computational fluid dynamics model during the coupling calculation process.

[0074] The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for analyzing local scour landforms of underwater pipelines, characterized in that: The following steps are involved: Obtain the local sand bed parameters and flow field parameters of the underwater pipeline to be tested and construct a model to obtain a discrete element model and a computational fluid dynamics model; Set boundary conditions for discrete element models and computational fluid dynamics models; Numerical simulation experiments were conducted based on the boundary condition coupling discrete element model and computational fluid dynamics model to obtain the simulated scour landform results; The boundary conditions of the discrete element model include: If the water flow rate is less than the preset threshold, it is set as a fixed boundary condition; If the water flow velocity is greater than a preset threshold, a periodic boundary condition is set in the water flow direction, and fixed boundary conditions are set in other directions; The boundary conditions of the computational fluid dynamics model include: excluding the position of the particle discrete element model, the remaining positions of the sand bed are set to no-slip wall boundary conditions, the top of the flow field is set to symmetric boundary conditions, the inlet is set to velocity inlet boundary conditions, and the outlet is set to pressure outlet boundary conditions; The step of performing a numerical simulation experiment based on boundary condition coupling of a discrete element model and a computational fluid dynamics model to obtain a simulated scour landform result specifically includes: Obtain the geometric dimensions of the space around the underwater pipeline to be tested and use the finite volume method to discretize the flow field to construct the computational fluid dynamics calculation grid; Obtain the flow field state and input it into the discrete element model for calculation to obtain the particle state; Among them, the flow field state includes the pressure and flow velocity of the flow field, and the particle state includes the particle displacement, velocity and acceleration; in the calculation process of the discrete element model, the particle material density and particle size are first obtained to determine the calculation step size, and then all the particles in the flow field are scanned once every time step to calculate the resultant force, velocity, angular velocity and position of each particle. When the particles are in contact, the normal superposition and tangential superposition of a particle are first calculated, and then the magnitude of the resultant force is calculated. The impulse equation is used to calculate the velocity and position of the particle after one time step; then, based on the tangential force on the particle, the angular velocity of the particle after one time step is calculated using the angular momentum equation. In this way, the motion and force conditions of all particles in the flow field can be calculated within one time step, and the motion trajectory of all particles over a period of time can be calculated; The particle state is input into the computational fluid dynamics model for calculation, the flow field state is calculated based on the proportion of particles in the finite volume method grid, and the results are updated; The updated results are input into the discrete element model for repeated iteration until the calculation is stopped at the set time to obtain the scour landform results.

2. A method for analyzing local scour landforms of underwater pipelines according to claim 1, characterized in that: The sand bed parameters include particle size gradation, particle accumulation friction angle and particle material density, and the flow field parameters include upstream flow velocity, friction flow velocity, velocity zero point, wave period, wave height and wave velocity.

3. A method for analyzing local scour landforms of underwater pipelines according to claim 2, characterized in that: It also includes physical parameter experiments on the particle accumulation in the sand bed parameters to obtain the particle size, density and internal friction angle of the particles.

4. The method for analyzing local scour landforms of underwater pipelines according to claim 1, characterized in that: The inlet flow velocity uses a logarithmic flow distribution, and its calculation equation is as follows: In the above formula, u f is the frictional velocity, and z0 is the velocity zero point.

5. The method for analyzing local scour landform of underwater pipeline according to claim 1, characterized in that: It also includes coupling calculation to perform two-dimensional simulation when the direction of the underwater pipeline to be tested is perpendicular to the direction of water flow.

6. The method for analyzing local scour landforms of underwater pipelines according to claim 1, characterized in that: During the coupling calculation process, the discrete element model has more calculation times than the computational fluid dynamics model.

7. The method for analyzing local scour landforms of underwater pipelines according to claim 1, characterized in that: Set the Courant number of the computational fluid dynamics model to less than 1.

Images