A method for calculating water level fluctuation

Abstract

The present invention belongs to the technical field of water conservancy engineering, and specifically relates to a method for calculating water level fluctuations. The method adopts a method combining computational fluid dynamics with field measured data inversion, studies the hydraulic characteristics of a typical building in the middle line of a water conservancy project under the condition of large-flow water delivery, can theoretically analyze and study the flow state changes and water level fluctuation processes of hydraulic structures, and the obtained numerical simulation calculation results are basically consistent with the measured data, providing technical support and theoretical basis for the safe dispatching and operation of large-flow water delivery in the middle line of the water conservancy project, and providing certain guidance for the safe dispatching of large-flow water delivery, so that the project can give full play to the project benefits under the premise of ensuring safe operation.

Description

Technical Field

[0001] The invention belongs to the technical field of water conservancy projects, relates to the field of water level fluctuation calculation of hydraulic structures, and specifically relates to a water level fluctuation calculation method. Background Art

[0002] A water conservancy project is a strategic project for water resource allocation in my country, mainly to solve the problem of water shortage in some parts of my country. Since the first phase of the middle line of the project was put into operation in 2014, it has been running smoothly as a whole and has been running safely for 5 years. However, when the project is in high-flow water delivery conditions, some typical buildings such as aqueducts and inverted siphons and the inlets and outlets connected to the channels have obvious water level fluctuations, and vortices, backflows, turbulence or water scouring have occurred locally; the water level in front of some typical buildings is high, which may affect or increase local head losses, causing engineering safety hazards and affecting the safe scheduling and operation of the project.

[0003] Numerical simulation is a specific computational method that uses numerical calculation and image display to achieve the purpose of studying engineering problems, physical problems and various problems in nature. The process is: first, a mathematical model is established according to the problem, then a differential equation reflecting the relationship between the various quantities of the problem and the corresponding solution conditions are established, and finally a calculation method is selected for efficient and accurate calculation. However, the problems that need to be solved in numerical simulation are relatively complex, and the current numerical solution methods are not perfect in theory. The simulation effect of water flow changes and water level fluctuations during large-flow water transfer is not ideal. Therefore, a calculation method for water level fluctuations of hydraulic structures is urgently needed to simulate water level fluctuations. Summary of the invention

[0004] In view of the obvious water level fluctuations in the current large-flow water delivery conditions and the defects and problems of the current numerical simulation methods being imperfect, the present invention provides a water level fluctuation calculation method based on Flow-3D numerical analysis software.

[0005] The solution adopted by the present invention to solve the technical problem is: a water level fluctuation calculation method, comprising the following steps:

[0006] Step 1: Establish a solid domain model in ANSYS finite element software according to the calculation scale and the length of the actual straight section of the channel and the length of the upstream and downstream channel sections of the model;

[0007] Step 2: Use SolidWorks software to convert the established model into STL format that can be recognized by Flow-3D software, and import it into Flow-3D software. Add the fluid domain model on the basis of the solid domain model, and then use Flow-3D fluid calculation software to perform mesh division of the solid domain model and the fluid domain model.

[0008] Step 3: Check the mesh quality. If the mesh quality is unqualified, re-divide the mesh. If the mesh quality is qualified, set the boundary conditions and initial conditions of the model.

[0009] Step 4: Establish the continuity equation and momentum equation of incompressible viscous fluid as the control equations to study the interaction force between fluid and solid to describe the movement of water; analyze the constitutive calibration of the model, compare it with the field measured data and select the appropriate turbulence model;

[0010] Step 5. Input the basic parameters of the water delivery conditions into the Flow-3D software, calculate the Reynolds number of the model under different conditions, use the selected turbulence model for numerical simulation analysis, calculate the flow velocity, water depth, and water level fluctuations of the model, and analyze the characteristics of the tail pier shedding vortex.

[0011] In the above-mentioned water level fluctuation calculation method, the control equation adopts the continuity equation and momentum equation of incompressible viscous fluid, and the continuity equation is:

[0012]

[0013] Where: u, v, w are the velocity components in the x, y, z directions respectively; Ax, Ay, Az are the flowable area fractions in the x, y, z directions respectively;

[0014] The momentum equation is:

[0015]

[0016]

[0017]

[0018] Where: G x , G y , G z The gravitational acceleration in the x, y, and z directions, m / s 2 ;f x 、f y 、f z are the viscosity forces in the x, y, and z directions respectively; V F is the flowable volume fraction; ρ is the fluid density, kg / m 3 ; p is the pressure acting on the fluid element.

[0019] In the above-mentioned method for calculating water level fluctuation, step 2 also includes encrypting the grid at the model water level wave.

[0020] In the above-mentioned method for calculating water level fluctuation, the turbulence model is one or more of the four turbulence models: k-ω, k-ε, RNG k-ε, and LES.

[0021] The above water level fluctuation calculation method, in order to correct the turbulent viscosity, considers the influence of swirling flow on turbulence so as to better handle transient flow and flow state with large curvature. The turbulence model selects RNG k-ε model, and its turbulent kinetic energy k is:

[0022]

[0023] Its consumption rate ε:

[0024]

[0025] Where: G k represents the turbulent kinetic energy generation term caused by the average velocity gradient, G b It is expressed as the term of turbulent kinetic energy generated by buoyancy, Y M It is expressed as the effect of the pulsating expansion of the compressible turbulent kinetic energy flow on the total dissipation rate, α k , α s represents the calculation of the inverse of the effective Prandtl number of k and ε, where the model constant C 1ε =1.42, C 2ε =1.68.

[0026] The above-mentioned water level fluctuation calculation method includes the calculation of the tail pier lift coefficient and Strouhal number for the analysis of the tail pier shedding vortex characteristics, where the lift coefficient is calculated using:

[0027]

[0028] Where, Fl is the lift force on the tail pier; ρ is the fluid density; U is the average flow velocity at the outlet of the aqueduct; D is the characteristic length of the tail pier;

[0029] The Strouhal number is calculated using:

[0030]

[0031] Where St is the Strouhal number, f st is the frequency of tail vortex shedding, U is the average flow velocity at the aqueduct outlet; D is the characteristic length of the tail pier.

[0032] The above-mentioned water level fluctuation calculation method divides the gridded model into structured grid blocks, and the adjacent boundaries of each grid block are set as symmetric boundaries; the bottom boundary and left and right wall boundaries of each grid block are set as wall boundaries; and the top boundary of each grid block is set with a symmetric boundary.

[0033] Beneficial effects of the present invention:

[0034] 1. This method takes into account the actual operation of the first phase of the central line of a water conservancy project. It uses a method that combines computational fluid dynamics with inversion of field measured data to study the hydraulic characteristics of typical buildings in the central line of the water conservancy project under large-flow water delivery conditions, providing technical support and theoretical basis for the safe scheduling and operation of large-flow water delivery in the project, and providing certain guidance for the safe scheduling of large-flow water delivery in typical buildings in the central line of the project, so that the central line of the water conservancy project can give full play to the project benefits while ensuring safe operation.

[0035] 2. This method is a calculation method based on Flow-3D large-scale numerical simulation fluid software. The software can accurately and efficiently simulate and analyze hydraulic structures under different working conditions, realizing the effective combination of engineering practice and numerical simulation.

[0036] 3. This method uses field measured data to set model parameters and initial conditions, and the numerical simulation calculation results are basically consistent with the measured data, which ensures the feasibility of the method and the accuracy of the calculation, and provides a strong guarantee for realistically simulating the dynamic process of water surface fluctuations of typical buildings.

[0037] 4. By analyzing the numerical simulation results of the water level fluctuations obtained by this method, corresponding solutions can be proposed for the calculated model to control the water level fluctuations, so that the actual project can give full play to the project benefits while ensuring safe operation.

[0038] 5. The calculation process used in the present invention has clear physical concepts and a simple calculation process, and is easy to implement in the Flow-3D software, so as to facilitate processing and solving a series of problems caused by complex water level fluctuations that occur during the operation of hydraulic structures. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 The figure is a flow chart of the method of the present invention.

[0040] Figure 2 This is the Baihe inverted siphon-channel simulation model.

[0041] Figure 3 Schematic diagram of the hexahedral mesh division of the Baihe inverted siphon-channel model.

[0042] Figure 4 Schematic diagram of the grid division of the Baihe inverted siphon-channel model.

[0043] Figure 5 This is a cloud map of flow velocity changes at the outlet of the Baihe inverted siphon.

[0044] Figure 6 This is a cloud map of the water depth changes in the Baihe River inverted siphon.

[0045] Figure 7 This is a curve of water depth variation at the outlet of Baihe inverted siphon 1.

[0046] Figure 8 This is a curve of water depth variation at the outlet of Baihe inverted siphon 2.

[0047] Fig. 9 This is a curve of water depth variation at the outlet of Baihe inverted siphon 3.

[0048] Fig.10 This is a curve of water depth variation at the outlet of Baihe inverted siphon 4.

[0049] Fig.11 This is the time history curve of the lift coefficient of the tail pier D1 of the Baihe inverted siphon outlet chamber section.

[0050] Fig.12 This is the time history curve of the lift coefficient of the tail pier D2 of the Baihe inverted siphon outlet chamber section.

[0051] Fig.13 This is the time history curve of the lift coefficient of the tail pier D3 of the Baihe inverted siphon outlet chamber section.

[0052] Fig.14 This is the lift coefficient spectrum of the tail pier D1 of the Baihe inverted siphon outlet chamber section.

[0053] Fig.15 This is the lift coefficient spectrum of the tail pier D2 of the Baihe inverted siphon outlet lock chamber section.

[0054] Fig.16 This is the lift coefficient spectrum of the tail pier D3 of the Baihe inverted siphon outlet chamber section. DETAILED DESCRIPTION

[0055] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0056] Example 1: In order to better explain the technical solution of the present invention in detail, this example takes the Baihe inverted siphon project as an example for detailed explanation.

[0057] The Baihe inverted siphon project is 1,337 meters long in total and is divided into 77 sections (each section is about 14.8 meters long). It is a concrete pipe with two holes in a connection, a total of four holes, and the net size of a single hole pipe is 6.7×6.7 meters.

[0058] The Baihe Inverted Siphon Project crosses the bottom of the Baihe River. The project uses the pressure of the water flow in the channel to enter the riverbed from the inlet and then exit from the outlet. This ensures the normal water delivery, irrigation, and flood discharge requirements of the Baihe River, as well as the water quality requirements. The design flow of the Baihe Inverted Siphon Project is 330m 3 / s, increase the flow rate to 400m 3 / s, the designed discharge flow of the water discharge gate is 165m 3 / s. The main buildings of the project from the inlet to the outlet are: inlet gradient section, water discharge gate and transition section, inlet inspection gate, inverted siphon pipe body, outlet control gate (inspection gate), outlet gradient section.

[0059] The typical inverted siphon project selected the high-flow water delivery condition of the Baihe inverted siphon project for numerical simulation. During the high-flow water delivery period of the Baihe inverted siphon, the gate is open and the water level fluctuation phenomenon will occur at the outlet where the Baihe inverted siphon connects with the channel. The unstable water flow increases the difficulty of flow control and operation management. Therefore, this embodiment studies the water flow changes and water level fluctuations that occur during the high-flow water delivery process of the Baihe inverted siphon. The method flow chart is as follows: Figure 1 shown.

[0060] 1. Modeling

[0061] According to the design drawings of Baihe inverted siphon, a three-dimensional numerical simulation model of Baihe inverted siphon was established in ANSYS finite element software. Figure 2 As shown. In this embodiment, the Baihe inverted siphon-channel model is selected as the pipe body section and the outlet section gradient section. The main reasons are as follows: ① According to the on-site investigation, the water depth at the inlet of the Baihe inverted siphon changes steadily, and there is no local vortex, backflow and other phenomena in the water body; however, there are large fluctuations in water levels in the Baihe outlet lock chamber section and the outlet connection section. ② The length of the Baihe inverted siphon pipe body section is greater than 1000m. Under normal operating conditions of the project, the water flow in the inverted siphon pipe body is a constant flow, and the water flow characteristics of each section are basically the same; considering the computer performance and the economy of calculation, this calculation only selects the Baihe inverted siphon outlet part for modeling.

[0062] The positive direction of the model X is selected as the direction of the river flow, the Y direction is perpendicular to the direction of the river flow, and the positive direction is perpendicular to the left bank, and the Z direction is perpendicular to the direction of the river flow, and the positive direction is upward. The model is converted into an STL format that can be recognized by the Flow-3D software through SolidWorks software, and imported into the Flow-3D model. Then, the Flow-3D fluid calculation software is used to mesh the model. The Flow-3D software is used to perform hexahedral meshing on the Baihe inverted siphon-channel model. The meshing is as follows: Figure 3 As shown in the figure, the total number of divided grids is 14,848,780, of which the total number of fluid grids is 10,299,321 and the total number of solid grids is 2,099,365.

[0063] 2. Model boundary conditions and initial conditions setting

[0064] 1. Boundary condition division

[0065] Flow-3D provides several different boundary conditions, including:

[0066] ①Symmetry boundaries;

[0067] ② Wall boundaries;

[0068] ③Continuous boundary conditions (Continuative boundaries);

[0069] ④Periodic boundaries;

[0070] ⑤ Specified pressure boundaries;

[0071] ⑥ Specified velocity boundaries;

[0072] ⑦Grid overlay boundaries;

[0073] ⑧ Free outflow boundary conditions (Outflow boundaries);

[0074] ⑨Wave boundaries;

[0075] ⑩Volumetric flow rate boundaries.

[0076] The Flow-3D software presents the physical model after grid modularization in the form of Cartesian three-dimensional coordinates. Each structured grid block can be given 6 boundary conditions according to the coordinates. Due to the irregular structure of the numerical simulation calculation model of the Baihe Inverted Siphon, the Baihe Inverted Siphon is divided into 3 structured grid blocks. The adjacent boundaries of each grid block are set as symmetric boundaries (Symmetry); the upstream inlet boundary is set as the volumetric flow rate boundary (Volumetric flow rate), the flow value must be positive, and the default direction is to enter the grid; the downstream outlet boundary is set as the velocity outlet boundary (Specifiedvelocity); the bottom boundary and the left and right wall boundaries of the three grid blocks are set as wall boundaries (Wall), where the normal velocity of the wall is zero, so that the tangent velocity at the wall is equal to zero, which conforms to the actual flow velocity distribution; the top boundary is set as a symmetric boundary (Symmetry). The model boundary conditions are set as follows Figure 4 shown.

[0077] 2. Model initial condition setting

[0078] If the calculation of the Baihe inverted siphon model simulates the process from the pipe body and channel being waterless to being fully filled with water, a lot of calculation time is required, and the water body oscillation in the calculation results cannot be eliminated in a short time. In order to improve the calculation efficiency, this numerical simulation calculation sets the initial water body in the pipe body section and the outlet channel section to reduce the calculation time. The setting of the initial water body height of the outlet channel section should be based on the downstream water level, and the water level of each section is calculated by interpolation.

[0079] According to the Flow-3D software, the initial conditions (initial water height), output conditions and numerical calculation conditions of the model are set respectively.

[0080] The output conditions are to set the type and interval of the required data output by the software according to the data calculation requirements; the numerical calculation conditions are the model calculation parameters that need to be set according to the actual data on site.

[0081] Set the fluid properties to single-phase incompressible liquid (One fluid, Free surface or sharp), select SI units for calculation, the fluid type is 20°C water, gravity is negative along the Z axis, and the gravity acceleration is -9.81m / s 2 The initial time step is 0.002 and the minimum time step is 10 -7 After the model is established, preprocess the numerical model in the numerical calculation area (Simulate). If an error message appears, check the parameter settings. Otherwise, run the simulation.

[0082] Before calculating the fluid-solid interface, it is necessary to establish the control equation based on the interaction force between the water body and the building. This numerical model calculates the movement of incompressible viscous fluid, and the control equations involved are the Navier-Stokes (NS) equations, including the continuity equation and momentum equation.

[0083] (1) Continuity equation. The expression of the continuity equation is:

[0084]

[0085] Where: u, v, w are the velocity components in the x, y, z directions respectively; Ax, Ay, Az are the flowable area fractions in the x, y, z directions respectively.

[0086] (2) Momentum equation. The expression of the momentum equation is:

[0087]

[0088]

[0089]

[0090] Where: G x , G y , G z are the gravitational acceleration in the x, y, and z directions, m / s2; f x 、f y 、f z are the viscosity forces in the x, y, and z directions respectively; V F is the flowable volume fraction; ρ is the fluid density, kg / m3; p is the pressure acting on the fluid element.

[0091] 3. Numerical simulation analysis of large flow water delivery conditions

[0092] The Reynolds number is the most basic dimensionless parameter in viscous fluid motion. When performing numerical simulation analysis on a model, the Reynolds number under different working conditions of the model must first be calculated to confirm whether the problem being analyzed conforms to the motion characteristics of viscous fluids.

[0093] Under the condition of large flow water delivery by inverted siphon of Baihe River, the water delivery flow is 315m 3 / s, the characteristic velocity U of the inverted siphon outlet chamber section is 1.16m / s, the hydraulic radius R is 5.44m, and the kinematic viscosity v is 1.003×10 6 m 2 / s, and the Reynolds number Re at the aqueduct inlet is calculated according to the Reynolds number formula to be 6.31×10 6 ;

[0094]

[0095] Where: ρ is the fluid density, U and L represent the characteristic velocity and characteristic length of the flow field respectively. For open channels and natural rivers, the characteristic length L is generally taken as the hydraulic radius R of the water-passing section, μ and v represent the dynamic viscosity coefficient and kinematic viscosity coefficient of the fluid respectively.

[0096] Then, according to the critical Reynolds numbers of the open channel and the natural river, it can be judged that the water flow in the outlet chamber section is in a turbulent state under the condition of large-flow water delivery of the Baihe inverted siphon.

[0097] The constitutive calibration of the analytical model is compared with the field measured data, and the model with better simulation effect is selected from the four turbulence models of k-ω, k-ε, RNG k-ε, and LES. Among them:

[0098] (1) k-ε model: The mathematical equations of the k-ε two-equation turbulence model include the K equation (turbulent kinetic energy equation) and the ε equation (turbulent kinetic energy dissipation rate equation). It is applicable to areas with large Reynolds numbers, especially to free shear laminar flows with small pressure gradients. It is the most commonly used turbulence model in engineering applications. However, this model performs poorly in simulating strong swirls, curved boundary layers, unconstrained flows, etc.

[0099] The transport equation of turbulent kinetic energy K is as follows:

[0100]

[0101] Where: P T is the turbulent kinetic energy generation term, G T For the buoyancy end, is the turbulent kinetic energy diffusion term, ε T is the dissipation term of turbulent kinetic energy.

[0102] The transport equation for the turbulent kinetic energy dissipation rate ε is as follows:

[0103]

[0104] In the formula, CDIS1, CDIS2, and CDIS3 are custom coefficients, and their default values ​​in the model are 1.44, 1.92, and 0.2, respectively.

[0105] (2) RNG k-ε model

[0106] Swirl plays an important role in turbulence. The standard k-ε model does not perform well in dealing with fluids with large curvatures. To make up for this shortcoming, the RNG k-ε model corrects the turbulent viscosity on this basis, so that it can better deal with transient flows and flows with large curvatures. The control equations of the RNG k-ε model are similar to those of the standard k-ε model, but the coefficients of the two are different. Generally, the RNG k-ε model has a wider range of applications. The k equation and ε equation in the RNG k-ε model are similar to those in the standard k-ε model, and its diffusion equation ε can be expressed as follows:

[0107] For the turbulent kinetic energy k:

[0108]

[0109] For the consumption rate ε:

[0110]

[0111] Where: G k represents the turbulent kinetic energy generation term caused by the average velocity gradient, G b It is expressed as the term of turbulent kinetic energy generated by buoyancy, Y M It is expressed as the effect of the pulsating expansion of the compressible turbulent kinetic energy flow on the total dissipation rate, α k , α s represents the calculation of the inverse of the effective Prandtl number of k and ε, where the model constant C 1ε =1.42, C 2ε=1.68. The RNG model can take into account the influence of rotational flow on turbulence, so in terms of vortex simulation, the model has a better response to turbulence than the standard model.

[0112] (3) k-ω model:

[0113] The k-ω model is a model based on turbulent kinetic energy k and specific dissipation rate ω (ε / k). Under certain flow conditions, the k-ω model is superior to the standard k-ε model and RNG k-ε, such as jets that are close to wall boundaries and have flow pressure gradients. The equation expression of the k-ω model is:

[0114]

[0115] In the formula, β * =0.09, the RMTKE of the diffusion term is 1 / 2;

[0116] The transport equation for the specific dissipation rate ω is as follows:

[0117]

[0118] In the formula: α=13 / 25, RMDTKE=1 / 2, β=9 / 125, ε=β*kω, v T =k / ω.

[0119] (4) Large Eddy Model

[0120] Large Eddy Simulation (LES) is a turbulence numerical simulation method between direct numerical simulation (DNS) and Reynolds averaging method (RANS). When simulating turbulent motion numerically, only eddies larger than the grid size are calculated directly through the Navier-Stokes equations, while small-scale eddies can be represented by a model and only play a dissipative role. They are almost isotropic. Therefore, the LES method aims to simulate large-scale eddies using the unsteady NS equations, but does not directly calculate small-scale eddies. The influence of small eddies on large eddies is considered through an approximate model, and this influence can be described by a turbulent viscosity coefficient.

[0121] The basic idea of ​​large eddy numerical simulation is to directly calculate the large-scale pulsation and use an approximate model to calculate the small-scale pulsation. The most important thing to achieve large eddy numerical simulation is to separate the direct large-scale pulsation and the small-scale pulsation.

[0122] In the large eddy simulation method, a filter function is first established to divide the transient variables of the fluid into two parts, namely the large-scale average component and the small-scale component. The Navier-Stokes equation is filtered to obtain the following equation:

[0123]

[0124]

[0125] in, It is called subgrid stress (SGS), which represents the influence of small-scale eddies on the solution of the equation of motion. It is the momentum transfer between the filtered small-scale pulsation and the solvable scale turbulence. and A closed model of subgrid stresses must be constructed.

[0126] The more commonly used model is to use the eddy viscosity concept assumption, that is:

[0127]

[0128] Where, the sub-grid eddy viscosity coefficient is Δ is the filtering scale, C s Δ is equivalent to the mixing length, C s It is called the Smagorinsky constant.

[0129] After calculation and analysis, in this embodiment, when calculating the large flow water delivery condition of the Baihe River inverted siphon, the turbulence model selects the RNGk-ε model. In the actual operation of the project, the water delivery flow of the Baihe River inverted siphon is 315m 3 / s is a large flow water delivery condition.

[0130] According to the on-site measured data, under this working condition, the inlet water level is 140.55m and the outlet water level is 140.60m.

[0131] In the Flow-3D software, the boundary conditions of the calculation model were set, the basic parameters of the water delivery condition were input, the numerical simulation model was analyzed, and the flow velocity, water depth and water level fluctuation of the model were calculated; the model inlet was set as the flow inlet boundary, and the flow size was set to 315m 3 / s, the model outlet is set as the velocity outlet boundary, the velocity is 1.219m / s, and the water viscosity is set to 0.001N·s / m 2 , the roughness is set to 0.014, and the calculation time is set to 800s.

[0132] The results are analyzed as follows.

[0133] 1. Velocity cloud diagram results analysis

[0134] The velocity changes in the pipe body section are relatively uniform under the condition of large flow rate water delivery of Baihe Inverted Siphon, but the velocity changes greatly in the gate chamber section and gradient section of Baihe Inverted Siphon outlet. In order to facilitate the observation of water flow changes, the velocity color band is set to 0-2.5m / s. The flow change process is shown in the figure. Figure 5As shown, a total of 7 moments are selected for the velocity change cloud diagram.

[0135] It can be seen from the flow velocity distribution diagram that: in the Baihe inverted siphon outlet chamber section, due to the increase in flow cross-section, the flow velocity is lower than that in the pipe body section, and the flow velocity in the outlet chamber section changes alternately; irregular vortices appear behind the tail pier, and the vortices at each tail pier influence each other, resulting in fluctuations in the flow velocity on the side walls of the outlet gradient section; the maximum flow velocity appears in the outlet chamber section at 200s, and the maximum flow velocity reaches 2.5m / s.

[0136] 2. Analysis of water depth distribution results

[0137] (1) Water depth cloud map analysis

[0138] Under the condition of large flow rate water delivery of Baihe inverted siphon, the water depth of the pipe section does not change, but the water level fluctuation will occur in the gate chamber section of Baihe inverted siphon outlet. In order to facilitate the observation of water level changes, the water depth band is set to 0-8m. The flow pattern change process is as follows: Figure 6 As shown in the figure, corresponding to the velocity cloud diagram, the water depth cloud diagrams at 7 moments are taken for analysis.

[0139] It can be seen from the figure that there is a more obvious water level fluctuation phenomenon in the gate chamber section of the Baihe inverted siphon outlet. From the water depth cloud map before 400, it can be seen that the two middle troughs and the side troughs show alternating fluctuations. When the middle trough is the crest, the side trough is the trough, and the fluctuation amplitude of the two middle troughs is greater than that of the side troughs; from the water depth cloud map after 400, it can be seen that the two troughs on the left and the two troughs on the right fluctuate symmetrically. When the left trough is the crest, the left second trough is the trough, and the fluctuation amplitude of the two middle troughs is greater than that of the side troughs. The maximum water depth reaches 8m.

[0140] (2) Analysis of water level fluctuation time history diagram

[0141] The time-series curve of the water level fluctuation in the left and right troughs at the inlet of the Baihe inverted siphon is shown in Figure 7-10. For the convenience of observation, the time-series curve takes the time period of 300-800s.

[0142] From the water level fluctuation time-history curve, we can see that the water level fluctuation amplitude at the outlet of Baihe inverted siphon pipe 1 is 0.40m; the water level fluctuation amplitude at the outlet of pipe 2 is 0.24m; the water level fluctuation amplitude at the outlet of pipe 3 is 0.25m; and the water level fluctuation amplitude at the outlet of pipe 4 is 0.21m.

[0143] 3. Analysis of the characteristics of the tail pier shedding vortex

[0144] (1) Lift coefficient

[0145] Under high-flow water delivery conditions, the average flow velocity U at the outlet of the Baihe inverted siphon lock chamber section is 1.16m / s. The tail piers of the outlet lock chamber section are numbered D1, D2, and D3 from left to right, and the widths of the tail piers are 2m, 4m, and 2m respectively. The lift coefficient of each tail pier is obtained according to the lift coefficient calculation formula.

[0146]

[0147] Where, Fl is the lift force on the tail pier; ρ is the fluid density; U is the average flow velocity at the outlet of the aqueduct; D is the characteristic length of the tail pier;

[0148] The time history curves of the lift coefficient of each tail pier are as follows: Figure 11-13 As shown, the calculated results are extracted when the flow development is stable.

[0149] It can be seen from the figure that the lift coefficient Cl changes periodically, and the curve fluctuates up and down with 0 as the center, but its amplitude changes continuously with time. The amplitude of the lift coefficient curve fluctuates due to the mutual influence of the tail piers; the maximum amplitude of the tail pier D1 is 0.51; the maximum amplitude of the tail pier D2 is 0.10; the maximum amplitude of the tail pier D3 is 0.28.

[0150] (2) Strouhal number

[0151] Further fast Fourier transform (FFT) of the lift coefficient Cl is performed to obtain its spectrum analysis as follows Figure 14-16 shown.

[0152] From the figure, we can get: the vortex shedding frequency f of the tail pier D1 st1 is 0.206Hz; the vortex shedding frequency f of the tail pier D2 st2 is 0.061Hz; the vortex shedding frequency f of the tail pier D3 st3 The average flow velocity U at the Baihe inverted siphon outlet chamber is 1.16 m / s. According to the Strouhal number formula,

[0153]

[0154] Where St is the Strouhal number, f st is the frequency of tail vortex shedding, U is the average flow velocity at the aqueduct outlet; D is the characteristic length of the tail pier.

[0155] The calculated Strouhal number St of the tail pier D1 is 0.355; the Strouhal number St of the tail pier D2 is 0.210; and the Strouhal number St of the tail pier D3 is 0.353.

[0156] The above description is only a preferred embodiment of the present invention and does not limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for calculating water level fluctuations, characterized in that: The following steps are involved: Step 1: Establish a solid domain model in ANSYS finite element software according to the calculation scale and the length of the actual straight section of the channel and the length of the upstream and downstream channel sections of the model; Step 2: Use SolidWorks software to convert the established model into STL format that can be recognized by Flow-3D software, and import it into Flow-3D software. Add the fluid domain model on the basis of the solid domain model, and then use Flow-3D fluid calculation software to perform mesh division of the solid domain model and the fluid domain model. Step 2 also includes encrypting the mesh at the model water level wave; Step 3: Check the mesh quality. If the mesh quality is unqualified, re-divide the mesh. If the mesh quality is qualified, set the boundary conditions and initial conditions of the model. Step 4: Establish the continuity equation and momentum equation of incompressible viscous fluid as the control equations to study the interaction force between fluid and solid to describe the movement of water; analyze the constitutive calibration of the model, compare it with the field measured data and select the appropriate turbulence model; Step 5: Input the basic parameters of the water delivery condition into the Flow-3D software, calculate the Reynolds number of the model under different working conditions, use the selected turbulence model for numerical simulation analysis, calculate the flow velocity, water depth, water level fluctuation of the model, and analyze the characteristics of the tail pier shedding vortex; The turbulence model is one or more of the four turbulence models of k-ω, k-ε, RNG k-ε, and LES; The analysis of the shedding vortex characteristics of the tail pier includes the calculation of the tail pier lift coefficient and Strouhal number. Where, Fl is the lift force on the tail pier; ρ is the fluid density; U is the average flow velocity at the outlet of the aqueduct; D is the characteristic length of the tail pier; The Strouhal number is calculated using Where St is the Strouhal number, f st is the frequency of tail vortex shedding, U is the average flow velocity at the aqueduct outlet; D is the characteristic length of the tail pier.

2. The water level fluctuation calculation method according to claim 1, characterized in that: The control equation uses the continuity equation and momentum equation of the incompressible viscous fluid. The continuity equation is: Where: u, v, w are the velocity components in the x, y, and z directions respectively; Ax, Ay, Az are the flowable area fractions in the x, y, and z directions respectively; the momentum equation is: Where: G x , G y , G z The gravitational acceleration in the x, y, and z directions, m / s 2 ;f x 、f y 、f z are the viscosity forces in the x, y, and z directions respectively; V F is the flowable volume fraction; ρ is the fluid density, kg / m 3 ; p is the pressure acting on the fluid element.

3. The water level fluctuation calculation method according to claim 1, characterized in that: In order to correct the turbulent viscosity and consider the influence of rotational flow on turbulence so as to better handle transient flow and flow state with large curvature, the turbulence model selects RNGk-ε model, and its turbulent kinetic energy k is: Its consumption rate ε: Where: G k represents the turbulent kinetic energy generation term caused by the average velocity gradient, G b It is expressed as the term of turbulent kinetic energy generated by buoyancy, Y M It is expressed as the effect of the pulsating expansion of the compressible turbulent kinetic energy flow on the total dissipation rate, α k , α s represents the calculation of the inverse of the effective Prandtl number of k and ε, where the model constant C 1ε =1.42, C 2ε =1.

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4. The water level fluctuation calculation method according to claim 1, characterized in that: The gridded model is divided into structured grid blocks, and the adjacent boundaries of each grid block are set as symmetric boundaries; the bottom boundary and the left and right wall boundaries of each grid block are set as wall boundaries; and the top boundary of each grid block is set with a symmetric boundary.

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