Flow deflecting energy dissipation scouring numerical simulation method and equipment and storage medium

Abstract

The invention discloses a flip flow energy dissipation scouring numerical simulation method and device and a storage medium, and relates to the technical field of water conservancy projects. The method comprises the steps that a multiphase fluid model and physical parameters are set in a CFD solver, and a fluid control equation is solved; a particle set is generated in the DEM solver, and physical and mechanical parameters and interaction parameters of particles are set; the CFD solver calculates the acting force of the fluid on the particles based on the flow field information and transmits the acting force to the DEM solver; the DEM solver solves a particle motion equation according to the acting force, the motion state of the particles is updated, and the updated motion state of the particles is transmitted back to the CFD solver; the CFD solver solves the fluid control equation again according to the particle motion state, and the flow field information is updated. According to the method, the interaction process between the fluid and the particles is considered, information interaction between fluid distribution and particle movement is achieved, and the simulation precision of the hydraulic scouring process is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of hydraulic engineering, and particularly relates to a pick-up flow energy dissipation scour numerical simulation method and equipment based on CFD-DEM coupling and a storage medium. BACKGROUND

[0002] In the field of hydraulic engineering, the scour problem, especially the local scour around structures such as bridge piers and dams, is a key issue that widely exists and is related to the safety of engineering. Due to the extreme complexity of the topography of natural rivers and the limitations of on-site monitoring equipment and technology, it is difficult to effectively capture and analyze the internal physical mechanism of the local scour process through on-site observation means. Although the local scour can be studied through physical model flume experiments, such methods are often significantly affected by the model scale effect, resulting in uncertainty in the experimental results when extrapolated to actual engineering.

[0003] Under this background, computational fluid dynamics numerical simulation has become an important technical means for studying hydraulic scour problems. At present, researchers generally use CFD software based on the continuous medium hypothesis to simulate local scour. In such a model, both the fluid and the sediment are treated as continuous phases, the fluid motion is solved by solving the Navier-Stokes equation (N-S), and the sediment transport empirical formula is coupled to describe the migration of sediment. This method has shown a certain accuracy in predicting the scour depth under certain conditions, but its core limitation is that it cannot reveal the real interaction between particles and particles, and particles and fluid at the microscopic scale. The physical nature of local scour is precisely the initiation, transport and deposition process of discrete sediment under the action of a complex flow field.

[0004] In recent years, the computational fluid dynamics-discrete element coupling method (CFD-DEM) has shown its unique advantages as an advanced numerical technology for solving fluid-structure coupling problems at the particle scale. The CFD-DEM method uses the Euler framework to process the fluid phase, divides the calculation domain into grids and solves the N-S equation to obtain the fluid velocity, pressure and other field variables of each grid element; at the same time, the Lagrangian framework is used to process the solid phase, the sediment is regarded as a discrete collection of particles, the forces acting on each particle are calculated, and the transient changes of its acceleration, velocity and position are tracked according to Newton's second law. The core advantage of this method is that it can accurately simulate and record the motion trajectory and mechanical behavior of each particle.

[0005] Currently, the CFD-DEM method has been successfully applied in various fields such as aeolian sand movement, fluidized bed reactors, and pneumatic conveying, demonstrating its excellent engineering applicability. Introducing it into the study of scour problems, treating the solid phase as a discrete system, and accurately considering the interaction between the solid and liquid phases, while utilizing Lagrange particle tracking technology to capture detailed motion information of particle sediments, is expected to provide unprecedented insights into the in-depth exploration of local scour mechanisms, overcoming the inherent limitations of traditional continuous medium models. Summary of the Invention

[0006] In view of the above-mentioned defects in the existing technology, the purpose of this invention is to provide a numerical simulation method, device and storage medium for hydraulic scour, which takes into account the continuity of multiphase fluid and the discreteness of particles, and simulates the coupling process between fluid impact and particle motion more accurately, effectively predicts the dynamic change characteristics of scour pits, and provides theoretical guidance for hydraulic scour research and protection design.

[0007] This invention solves the above-mentioned technical problems through the following technical solution: a numerical simulation method for flow dissipation and scouring, comprising:

[0008] A three-dimensional geometric model of the energy dissipation channel is established, and the three-dimensional geometric model is meshed to generate a mesh model for fluid calculation.

[0009] The mesh model is imported into the CFD solver, the multiphase fluid model and physical parameters are set, and the fluid control equations are solved to obtain the initial flow field information.

[0010] In the DEM solver, a collection of particles is generated in the riverbed region at the bottom of the three-dimensional geometric model, and the physical and mechanical parameters of the particles, as well as the interaction parameters between particles and between particles and the riverbank, are set.

[0011] The CFD solver calculates the force exerted by the fluid on each particle in the particle set based on the flow field information at the current time step, and transmits the force to the DEM solver through a coupling interface.

[0012] The DEM solver solves the particle motion equations based on the received forces, updates the particle motion state at the new time step, and transmits the updated particle motion state back to the CFD solver through the coupling interface.

[0013] The CFD solver, based on the received particle motion state, treats the particles as internal moving boundaries, resolves the fluid control equations, and updates the flow field information.

[0014] The calculation and transmission of particle forces, the updating and transmission of particle motion states, and the updating of flow field information are repeated until convergence, thereby simulating the riverbed scouring process under jet flow energy dissipation.

[0015] In this embodiment, each sediment particle is treated as an independent entity in the DEM solver. When two particles come into contact, the normal elastic force, tangential friction force, and damping force between the particles are calculated in real time based on the set physical and mechanical parameters (e.g., shear modulus, coefficient of restitution) and interaction parameters (static friction coefficient, dynamic friction coefficient). This directly simulates the energy dissipation of particle collisions, the friction force formed by particle stacking, and the force transmission of particles during rolling. This achieves the simulation of the actual interaction between particles during local scouring, solving the problem that traditional CFD methods treat sediment as a continuous whole field and cannot simulate the collision, friction, and compression behaviors between particles.

[0016] This invention enables bidirectional real-time transmission and joint iterative calculation of fluid phase and particle phase data through a coupling interface, realizing the visualization and quantification of microscopic physical processes. It solves the problem that traditional methods can only provide the final scouring morphology and cannot reproduce the specific process of particles moving from rest to motion.

[0017] Furthermore, the three-dimensional geometric model is divided into polyhedral meshes; wherein, the surface of the spillway is locally meshed and a boundary layer mesh is set in the downstream water surface area, and the boundary layer mesh has multiple layers.

[0018] In this embodiment, the use of polyhedral meshes improves computational accuracy and convergence speed; local mesh refinement of the spillway surface improves the computational accuracy of the shear force of the water flow relative to the wall, which can realistically reflect the guiding effect of the sill on the water flow and ensure the accuracy of the prediction of jet trajectory, velocity and diffusion degree; setting a boundary layer mesh in the downstream water surface area helps to more realistically simulate details such as splashing, surface ripples and aeration phenomena.

[0019] Furthermore, the multiphase fluid model is a two-phase fluid model, including a water phase and an air phase, and the physical parameters include the density and dynamic viscosity of water, the density and dynamic viscosity of air, and the surface tension coefficient between water and air.

[0020] Furthermore, the physical and mechanical parameters of the particles include particle density, Poisson's ratio, and shear modulus; the interaction parameters include the collision recovery coefficient, static friction coefficient, and rolling friction coefficient between particles and between particles and the riverbank.

[0021] Furthermore, the fluid control equations include a continuity equation and a momentum equation, specifically expressed as follows: ; ; , ; in, This represents the volume fraction weighted average density. The velocity components of the fluid within the grid are represented by i = x, y, z, and j = x, y, z, corresponding to the x, y, and z directions, respectively. Indicates time; Represents grid space coordinates; Indicates pressure; This represents the volume-weighted average molecular viscosity coefficient. Indicates turbulent viscosity; Indicates the volume fraction of water; Indicates water flow density; Indicates the volume fraction of air; Indicates air density; This indicates the viscosity of water molecules; This indicates the viscosity of air molecules.

[0022] Furthermore, the VOF model is used to solve the water-air two-phase interface. By solving for the volume fraction of water, the free liquid surface is captured. The solution expression is: ; .

[0023] Furthermore, the force exerted by the fluid on each particle in the particle assembly includes dragging force and lifting force; wherein, the specific calculation formula is as follows: ; ; ;

[0024] in, This represents the force exerted by the fluid on the particles; This represents the upward force exerted by the fluid on the particles; This indicates the drag force of the fluid on the particles; This represents the lift coefficient of the fluid on the particles; This represents the shape factor of the lifting force area. Converted into an effective projected area perpendicular to the direction of the lifting force; The characteristic length of a particle is indicated by its equivalent diameter. Indicates water flow density; Indicates the speed of water flow; Represents gravitational acceleration; This represents the drag force coefficient of the fluid on the particles; The drag force area shape factor represents the drag force. Converted into an effective projected area perpendicular to the direction of water flow.

[0025] Furthermore, the specific expression of the particle motion equation is as follows: ; ; ; ; ; in, Indicate the mass of particles i and j; The velocity of particle i after the collision is represented by t; time is represented by t. This represents the normal elastic force between particles; This represents the normal damping force between particles; This represents the tangential elastic force between particles; This represents the tangential damping force between particles; This represents the force exerted by the fluid on particle i; Represents gravitational acceleration; Indicates the equivalent Young's modulus; Indicates the equivalent radius; Indicates the amount of normal overlap between particles; Let i and j represent the Young's modulus of particles i and j, respectively. , Let i and j represent the Poisson's ratios of particles i and j, respectively. Let i and j represent the radii of particles i and j, respectively. This represents the damping coefficient associated with the coefficient of restitution e; Indicates the normal contact stiffness between particles; Indicates equivalent mass; Represents the normal relative velocity; e represents the coefficient of restitution for particle collisions; Indicates the tangential contact stiffness between particles; Indicates the tangential overlap between particles; This represents the tangential relative velocity.

[0026] Based on the same concept, the present invention also provides an electronic device, including a memory, a processor, and a computer program or instructions stored in the memory, wherein the processor executes the computer program or instructions to implement the numerical simulation method for scouring and dissipating energy as described above.

[0027] Based on the same concept, the present invention also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implements the numerical simulation method for flow dissipation and scouring as described above.

[0028] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0029] This invention realizes the fluid-structure interaction process of water flow and particle motion, which can capture the motion trajectory of particles more accurately. It considers the interaction process between fluid and particles, realizes the information exchange between fluid distribution and particle motion, and can not only capture the motion trajectory of particles under the impact of water flow, but also capture the dispersed seepage state of water flow in the particle group.

[0030] This invention sets the physical properties of multiphase fluids (water and air) and particles, while considering the continuity of multiphase fluids and the discreteness of particles. It performs coupled calculations of the flow field and particle field at each time step, which can more accurately simulate the interaction between water flow impact and particle motion. The calculation completes the range and depth of the resulting scour pit, providing theoretical guidance for hydraulic scour research and protection design. Attached Figure Description

[0031] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only one embodiment of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart of the numerical simulation method for energy dissipation and scouring in an embodiment of the present invention;

[0033] Figure 2 This is a schematic diagram of the three-dimensional geometric model of the energy dissipation channel in an embodiment of the present invention;

[0034] Figure 3 This is a schematic diagram of the three-dimensional geometric model mesh division of the energy dissipation channel in an embodiment of the present invention;

[0035] Figure 4 This is a schematic diagram of the particle set when the calculation time is 0 in an embodiment of the present invention;

[0036] Figure 5 This is a graph showing the particle motion caused by fluid impact when the calculation time is approximately 300 seconds in an embodiment of the present invention.

[0037] Figure 6 This is a diagram showing the coupling force results experienced by the particles when the calculation time is approximately 300 seconds in an embodiment of the present invention.

[0038] Figure 7 This is a diagram showing the elevation change of the lowest point of the scour pit in an embodiment of the present invention. Detailed Implementation

[0039] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0041] Example 1

[0042] To address the issue that scour studies often fail to consider the complex motions between actual particles, this invention provides a numerical simulation method for energy dissipation scour based on CFD-DEM coupling. For example... Figure 1 As shown, this numerical simulation method includes the following steps:

[0043] Step S1: Establish a three-dimensional geometric model of the jet flow energy dissipation channel, and mesh the three-dimensional geometric model to generate a mesh model for fluid calculation.

[0044] A three-dimensional geometric model of the diversion flow energy dissipation channel was established using 3D modeling software. A diversion flow energy dissipation channel refers to a complete hydraulic system that uses diversion flow to dissipate energy, typically consisting of three parts: spillway structures (such as spillways and flood tunnels), diversion sills, and the downstream channel.

[0045] In a specific embodiment of the present invention, the three-dimensional geometric model is divided into polyhedral meshes; wherein, the surface of the spillway is locally meshed and a boundary layer mesh is set in the downstream water surface area, and the boundary layer mesh has multiple layers.

[0046] Using polyhedral meshes improves computational accuracy and convergence speed; local mesh refinement on the spillway surface improves the computational accuracy of the shear force of the water flow relative to the wall, which can realistically reflect the guiding effect of the sill on the water flow and ensure the accuracy of the prediction of jet trajectory, velocity and diffusion degree; setting boundary layer meshes in the downstream water surface area helps to more realistically simulate details such as splashing, surface ripples and aeration phenomena.

[0047] Step S2: Import the mesh model generated in step S1 into the CFD solver, set the multiphase fluid model and physical parameters, and solve the fluid control equations to obtain the initial flow field information.

[0048] In this embodiment, the multiphase fluid model is a two-phase fluid model, namely a water phase and an air phase; the physical parameters include the density, viscosity and surface tension coefficient of each fluid phase, namely the density and dynamic viscosity of water, the density and dynamic viscosity of air, and the surface tension coefficient between water and air.

[0049] In a specific embodiment of the present invention, the fluid control equations include a continuity equation, a momentum equation, and a two-phase fluid motion equation; wherein, the expression for the continuity equation is:

[0050] (1)

[0051] (2)

[0052] The expression for the momentum equation is:

[0053] (3)

[0054] (4)

[0055] The VOF model is used to solve the two-phase fluid motion equations, and the specific expression is as follows:

[0056] (5)

[0057] (6)

[0058] in, This represents the volume fraction weighted average density. Represents the velocity components of the fluid (water, air, or a mixture of both) within the grid; i = x, y, z, j = x, y, z, corresponding to the x, y, and z directions in three-dimensional space, respectively. This represents the velocity component of the fluid within the grid in the x-direction; Indicates time; The grid space coordinates i = x, y, z, and j = x, y, z correspond to the x, y, and z directions in three-dimensional space, respectively. Indicates pressure; This represents the volume-weighted average molecular viscosity coefficient. Indicates turbulent viscosity; Indicates the volume fraction of water; This indicates the density of the water flow, i.e., the density of water. Indicates the volume fraction of air; Indicates air density; This indicates the viscosity of water molecules; This indicates the viscosity of air molecules.

[0059] In this embodiment, the flow field information includes the fluid's motion parameters, such as fluid density and velocity.

[0060] Step S3: In the DEM solver, generate a set of particles in the riverbed region at the bottom of the three-dimensional geometric model generated in step S1, and set the physical and mechanical parameters of the particles as well as the interaction parameters between particles and between particles and the river wall.

[0061] In this embodiment, the physical and mechanical parameters of the particles include the particle density, Poisson's ratio, and shear modulus, which can be obtained by consulting existing literature; the interaction parameters include the collision recovery coefficient, static friction coefficient, and rolling friction coefficient between particles and between particles and the river wall.

[0062] Step S4: The CFD solver calculates the force exerted by the fluid on each particle in the particle ensemble based on the flow field information at the current time step, and transmits this force to the DEM solver through the coupling interface.

[0063] In a specific embodiment of the present invention, the force exerted by the fluid on the particles includes dragging force and lifting force; wherein, the specific calculation formula is as follows:

[0064] (7)

[0065] (8)

[0066] (9)

[0067] in, This represents the force exerted by the fluid on the particles; This represents the upward force exerted by the fluid on the particles; This indicates the drag force of the fluid on the particles; This represents the lift coefficient of the fluid on the particles; This represents the shape factor of the lifting force area. Converted into an effective projected area perpendicular to the direction of the lifting force; The characteristic length of a particle is indicated by its equivalent diameter. This represents the water flow density, derived from the flow field information output by the CFD solver; This represents the water flow velocity, derived from the flow field information output by the CFD solver; Represents gravitational acceleration; This represents the drag force coefficient of the fluid on the particles; The drag force area shape factor represents the drag force. Converted into an effective projected area perpendicular to the direction of water flow.

[0068] Step S5: The DEM solver solves the particle motion equations based on the forces transmitted in step S4, updates the particle motion state at the new time step, and transmits the updated particle motion state back to the CFD solver through the coupling interface.

[0069] In a specific embodiment of the present invention, the specific expression of the particle motion equation is as follows:

[0070] (10)

[0071] (11)

[0072] (12)

[0073] (13)

[0074] (14)

[0075] (15)

[0076] (16)

[0077] (17)

[0078] (18)

[0079] (19)

[0080] in, Indicate the mass of particles i and j; The velocity of particle i after the collision is represented by t; time is represented by t. This represents the normal elastic force generated between particles due to elastic deformation. This represents the normal damping force generated during the collision of particles i and j. This represents the tangential elastic force between particles; This represents the tangential damping force between particles; This represents the force exerted by the fluid on particle i, which comes from the force output by the CFD solver. Represents gravitational acceleration; The equivalent Young's modulus is calculated from the Young's modulus and Poisson's ratio of two contacting particles i and j. Indicates the equivalent radius; This represents the normal overlap between particles, i.e., the depth to which particles i and j are pressed into each other; Let i and j represent the Young's modulus of particles i and j, respectively. Let i and j represent the Poisson's ratios of particles i and j, respectively. Let i and j represent the radii of particles i and j, respectively. This represents the damping coefficient associated with the coefficient of restitution e; Indicates the normal contact stiffness between particles; Indicates equivalent mass; Represents the normal relative velocity; e represents the coefficient of restitution for particle collisions; Indicates the tangential contact stiffness between particles; Indicates the tangential overlap between particles; This represents the tangential relative velocity.

[0081] The displacement of particle i is: .

[0082] Step S6: Based on the particle motion state returned from step S5, the CFD solver treats the particles as internal moving boundaries, resolves the fluid control equations, and updates the flow field information.

[0083] The CFD solver traverses each particle and determines which grid cell it is located in. For each grid cell, the total volume of all particles in it is calculated, and then the particle phase volume fraction and fluid phase volume fraction are calculated. The continuity equation and momentum equation are corrected based on the calculated fluid phase volume fraction. The corrected continuity equation ensures that the mass conservation of the fluid is based on the flowable area in the region containing particles. When correcting the momentum equation, the resistance of the particles to the fluid is added to the original momentum equation (Equation (3)) as an additional force term (added to the right side of Equation (3) by addition).

[0084] Step S7: Repeat steps S4 to S6 until convergence, thereby simulating the riverbed scouring process under the energy dissipation of the jet flow.

[0085] The CFD solver and DEM solver are coupled and cyclically calculated. The flow field information and particle motion information are updated in real time at each time step. The calculation is carried out together iteratively until the set time threshold is reached, thus realizing the simulation of the riverbed scouring process under the energy dissipation of the jet flow.

[0086] Example 2

[0087] Taking the energy dissipation and scouring process of a hydropower station as an example, the three-dimensional geometric model of the energy dissipation channel is established as follows: Figure 2 As shown, the mesh model after mesh generation is as follows: Figure 3As shown. In this embodiment, water flows out of the upstream reservoir and along the spillway, then falls into the downstream river channel after passing over the spillway embankment. The minimum size of the computational domain surface grid is 0.01 m, and the maximum size is 0.04 m. The surface grid of the spillway is locally refined, with a minimum surface grid size of 0.001 m and a maximum surface grid size of 0.02 m. A boundary layer grid is set on the downstream water surface to accurately capture the free surface distribution; the number of grid layers is 10, and the grid growth rate is 1.2. The entire computational domain is divided into polyhedral grids with a grid size of 0.04 m and a grid quantity of approximately 1.2 million.

[0088] In this embodiment, the fluid phases include water and air, with air as the first phase and water as the second phase. The upstream water level is 31.6875 m, and the downstream water level is 29.3525 m, flowing freely under gravity. The density of water is 1000 kg / m³. 3 The kinematic viscosity is 1.0*10. -6 m 2 / s, the density of air is 1.225 kg / m³ 3 The kinematic viscosity is 1.48*10. -5 m 2 / s, surface tension coefficient is 0.07 m / N. The two-phase flow motion is solved using the VOF model, tracing the water-air interface.

[0089] Figure 4 The particle set is shown when the computation time is 0. In this embodiment, the particles are spherical particles with a diameter of 1.07 cm, uniform particle size distribution, and a density of 2500 kg / m³. 3 Poisson's ratio is 0.25, and shear modulus is 10. 6 Pa, the collision recovery coefficient between particles is 0.5, the static friction coefficient is 0.3, the dynamic friction coefficient is 0.3, the collision recovery coefficient between particles and the river wall is 0.5, the static friction coefficient is 0.35, and the dynamic friction coefficient is 0.3.

[0090] Figure 5 The graph shows the results of fluid impact causing particle movement when the calculation time is approximately 300 s. The colored bands represent elevation values, i.e., the coordinate height of the particles after accumulation or the elevation of the crater, in mm. Figure 6 The diagram shows the coupling force on the particles when the calculation time is approximately 300 s. Figure 7 The elevation change diagram of the lowest point of the scour pit is shown. Figures 5 to 7It is evident that when the jet flows downstream, the impact force of the water flow exceeds the weight of the particles, causing them to move. This rapid particle movement leads to a rapid change in the depth of the scour pit, resulting in the initial formation of the scour pit's shape. Subsequently, as the water flow scours the surface, the particles on the pit move slowly, and the pit depth tends to stabilize. This is consistent with the scour pit formation process in actual engineering projects. Furthermore, the elevation of the lowest point of the scour pit obtained from the scour coupling simulation calculation matches the actual engineering measurement value well. This indicates that the scour coupling simulation technology can provide a reliable simulation method and parameter basis for the study of jet flow energy dissipation in hydraulic engineering.

[0091] Example 3

[0092] This invention also provides an electronic device, which includes a memory, a processor, and a computer program or instructions stored in the memory. The processor executes the computer program or instructions to implement the numerical simulation method for energy dissipation and scouring in this invention.

[0093] Although not shown, the electronic device includes a processor that can perform various appropriate operations and processes based on programs and / or data stored in read-only memory (ROM) or loaded from a storage portion into random access memory (RAM). The processor can be a multi-core processor or may contain multiple processors. In some embodiments, the processor may include a general-purpose main processor and one or more specialized coprocessors, such as a central processing unit, graphics processing unit (GPU), neural network processor (NPU), digital signal processor (DSP), etc. Various programs and data required for device operation are also stored in RAM. The processor, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0094] The processor and memory described above are used together to execute programs / instructions stored in the memory. When the program / instructions are executed by the computer, they can implement the methods, steps, or functions described in the above embodiments.

[0095] Although not shown, embodiments of the present invention also provide a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implements the numerical simulation method for flow dissipation and scouring in embodiments of the present invention.

[0096] Readable storage media include both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0097] The above description only discloses specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or modifications that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A numerical simulation method for energy dissipation and scouring of a flow, characterized in that, The numerical simulation method includes: A three-dimensional geometric model of the energy dissipation channel is established, and the three-dimensional geometric model is meshed to generate a mesh model for fluid calculation. The mesh model is imported into the CFD solver, the multiphase fluid model and physical parameters are set, and the fluid control equations are solved to obtain the initial flow field information. In the DEM solver, a collection of particles is generated in the riverbed region at the bottom of the three-dimensional geometric model, and the physical and mechanical parameters of the particles, as well as the interaction parameters between particles and between particles and the riverbank, are set. The CFD solver calculates the force exerted by the fluid on each particle in the particle set based on the flow field information at the current time step, and transmits the force to the DEM solver through a coupling interface. The DEM solver solves the particle motion equations based on the received forces, updates the particle motion state at the new time step, and transmits the updated particle motion state back to the CFD solver through the coupling interface. The CFD solver, based on the received particle motion state, treats the particles as internal moving boundaries, resolves the fluid control equations, and updates the flow field information. The calculation and transmission of particle forces, the updating and transmission of particle motion states, and the updating of flow field information are repeated until convergence, thereby simulating the riverbed scouring process under jet flow energy dissipation.

2. The numerical simulation method for energy dissipation and scouring according to claim 1, characterized in that, The three-dimensional geometric model is divided into polyhedral meshes; wherein, the surface of the spillway is locally meshed and a boundary layer mesh is set in the downstream water surface area, and the boundary layer mesh has multiple layers.

3. The numerical simulation method for energy dissipation and scouring according to claim 1, characterized in that, The multiphase fluid model is a two-phase fluid model, including a water phase and an air phase. The physical parameters include the density and dynamic viscosity of water, the density and dynamic viscosity of air, and the surface tension coefficient between water and air.

4. The numerical simulation method for energy dissipation and scouring according to claim 1, characterized in that, The physical and mechanical parameters of the particles include particle density, Poisson's ratio, and shear modulus; the interaction parameters include the collision recovery coefficient, static friction coefficient, and rolling friction coefficient between particles and between particles and the riverbank.

5. The numerical simulation method for energy dissipation and scouring according to claim 1, characterized in that, The fluid control equations include a continuity equation and a momentum equation, specifically expressed as follows: ； ； ， ； in, This represents the volume fraction weighted average density. The velocity components of the fluid within the grid are represented by i = x, y, z, and j = x, y, z, corresponding to the x, y, and z directions, respectively. Indicates time; Represents grid space coordinates; Indicates pressure; This represents the volume-weighted average molecular viscosity coefficient. Indicates turbulent viscosity; Indicates the volume fraction of water; Indicates water flow density; Indicates the volume fraction of air; Indicates air density; This indicates the viscosity of water molecules; This indicates the viscosity of air molecules.

6. The numerical simulation method for energy dissipation and scouring according to claim 5, characterized in that, The VOF model is used to solve the water-air two-phase interface. By solving for the volume fraction of water, the free liquid surface is captured. The solution expression is as follows: ； 。 7. The numerical simulation method for energy dissipation and scouring according to claim 1, characterized in that, The force exerted by the fluid on each particle in the particle assembly includes dragging force and lifting force; the specific calculation formula is as follows: ； ； ； in, This represents the force exerted by the fluid on the particles; This represents the upward force exerted by the fluid on the particles; This indicates the drag force of the fluid on the particles; This represents the lift coefficient of the fluid on the particles; This represents the shape factor of the lifting force area. Converted into an effective projected area perpendicular to the direction of the lifting force; The characteristic length of a particle is indicated by its equivalent diameter. Indicates water flow density; Indicates the speed of water flow; Represents gravitational acceleration; This represents the drag force coefficient of the fluid on the particles; The drag force area shape factor represents the drag force. Converted into an effective projected area perpendicular to the direction of water flow.

8. The numerical simulation method for jet flow energy dissipation and scouring according to any one of claims 1 to 7, characterized in that, The specific expression for the particle motion equation is as follows: ； ； ； ； ； in, Indicate the mass of particles i and j; The velocity of particle i after the collision is represented by t; time is represented by t. This represents the normal elastic force between particles; This represents the normal damping force between particles; This represents the tangential elastic force between particles; This represents the tangential damping force between particles; This represents the force exerted by the fluid on particle i; Represents gravitational acceleration; Indicates the equivalent Young's modulus; Indicates the equivalent radius; Indicates the amount of normal overlap between particles; Let i and j represent the Young's modulus of particles i and j, respectively. , Let i and j represent the Poisson's ratios of particles i and j, respectively. Let i and j represent the radii of particles i and j, respectively. This represents the damping coefficient associated with the coefficient of restitution e; Indicates the normal contact stiffness between particles; Indicates equivalent mass; Represents the normal relative velocity; e represents the coefficient of restitution for particle collisions; Indicates the tangential contact stiffness between particles; Indicates the tangential overlap between particles; This represents the tangential relative velocity.

9. An electronic device comprising a memory, a processor, and a computer program or instructions stored in the memory, characterized in that, The processor executes the computer program or instructions to implement the numerical simulation method for scouring and energy dissipation as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by the processor, they implement the numerical simulation method for scouring and energy dissipation as described in any one of claims 1 to 8.

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