Numerical Simulation Method and System for Coupling Turbulent Flow and Chemical Crystallization in Pipeline Based on Moving Mesh

Abstract

The present invention discloses a numerical simulation method and system for turbulent flow chemical crystallization coupling in pipelines based on dynamic meshes, which is used to simulate the crystallization blockage process of karst water in tunnel drainage pipelines in karst areas. This model attempts to establish a multi-field coupled hydrodynamic-chemical reaction coupling model to simulate the crystallization blockage process of karst tunnel drainage pipelines. The method provided by the present invention includes: constructing a crystallization blockage model of karst water in drainage pipelines considering the coupling of pipeline hydrodynamic field, concentration field and chemical reaction field, and simultaneously considering the crystallization blockage process of drainage pipelines under the combined action of temperature, ion concentration and flow velocity. The dynamic mesh equation is used to solve the displacement change of the boundary of the numerical model of drainage pipeline crystallization blockage, and then the numerical simulation of the crystallization blockage of karst tunnel drainage pipelines is carried out. The simulation technology provided by the present invention can provide technical support for the early identification and safety evaluation of karst tunnel blockages.

Description

Technical Field

[0001] The present invention relates to a numerical simulation method and system for coupling pipe turbulent flow chemical crystallization based on dynamic mesh, belonging to the technical field of hydrology and water resources. Background Art

[0002] In recent years, a large number of tunnel projects have been built in karst areas in China. The hydrogeological conditions in karst areas are complex, and tunnel water seepage and gushing disasters are frequent. Tunnel construction often requires a supporting drainage system. At present, there are various forms of tunnel waterproof and drainage designs in the industry.

[0003] However, in the actual production process, there is a lack of systematic research on the numerical simulation technology for predicting the dynamic process of crystal blockage in tunnel drain pipes and the precise control technology. The key scientific problem of drain pipe crystal blockage is to study the hydrodynamic characteristics and reactive solute transport process in the karst system in the drain pipe. Since the crystal blockage process is a complex process of fluid transport and chemical reaction coupling among various ions in karst groundwater, it is an extremely complex non-linear reactive solute transport system, including the multi-field coupling process of the seepage dynamic field in the rock pores during the karst groundwater seepage process, the dispersion field of solutes in low-permeability heterogeneous media, the water-rock interaction between karst groundwater and rock minerals, and the reactive chemical dynamic field generated by the dissolution-precipitation process of soluble salt components.

[0004] Studying the complex process of fluid transport and geochemical reaction coupling during the crystal blockage process, and then constructing a three-dimensional karst tunnel drainage system and reactive solute transport are the key technical means for accurately depicting the dissolution-precipitation during the crystal blockage process, and also the basis for realizing the precise quantification of crystal blockage. Summary of the Invention

[0005] Aiming at the lack of the above-mentioned prior art, the purpose of the present invention is to provide a numerical simulation method and system for coupling pipe turbulent flow chemical crystallization based on dynamic mesh. First, a reactive solute transport model suitable for tunnel drain pipes in karst areas is constructed, and the CaCO3 dissolution-precipitation process under the combined action of temperature, flow rate and concentration is considered. Then, it is applied to simulate the non-linear reaction system of multi-field coupling of complex seepage-dispersion-chemical reaction during the crystal blockage process of the drain pipe. The invention not only needs to consider the complexity of independent processes, but also solve the coupling relationship between various processes, and then realize the precise simulation and dynamic regulation of the crystal blockage process of the drain pipe based on dynamic mesh.

[0006] The present invention specifically adopts the following technical solutions: A numerical simulation method for coupling pipe turbulent flow chemical crystallization based on dynamic mesh, comprising the following steps:

[0007] Step SS1: Determine the model parameters of each physical field. The model parameters include: fluid density, flow velocity, fluid viscosity, turbulent kinetic energy, and turbulent dissipation rate of the turbulent k-ε model; convective mass transfer coefficient, surface reaction rate constant, activation energy, and saturation concentration of the chemical reaction model; normal grid velocity, fluid velocity, moving boundary smoothing adjustment parameter, and surface gradient operator of the dynamic grid equation.

[0008] Step SS2: Based on the model parameters collected in Step SS1, establish the reactive solute transport equation in the drainage pipe based on the principles of mass and energy conservation and the turbulent equation.

[0009] Step SS3: Determine the initial conditions, boundary conditions, hydraulic parameters, and source-sink terms of the reactive solute transport model, and perform spatial grid discretization and time discretization.

[0010] Step SS4: Solve the reactive solute transport model to obtain the distributions of the velocity vector and solute concentration in the simulation area in terms of time and space.

[0011] Step SS5: Based on the results of the reactive solute transport model obtained in Step SS4, establish a numerical model for crystal blockage in the karst tunnel drainage pipe based on the dynamic grid according to the dynamic grid equation.

[0012] Step SS6: Determine the initial conditions, boundary conditions, model parameters, and source-sink terms of the numerical model for crystal blockage in the drainage pipe in Step SS5, and perform spatial grid discretization and time discretization.

[0013] Step SS7: Solve the numerical model for crystal blockage in the karst tunnel drainage pipe to obtain the distributions of the velocity vector, solute concentration, and volume fraction of the generated crystals in the simulation area in terms of time and space after correction.

[0014] Step SS8: Depict the displacement change of the boundary of the numerical model for crystal blockage in the drainage pipe according to the changes in the flow field, concentration field, and crystal volume fraction, and complete the numerical simulation of crystal blockage in the karst tunnel.

[0015] As a preferred embodiment, both the reactive solute transport model in Step SS4 and the numerical model for crystal blockage in the drainage pipe in Step SS7 include a turbulent model and a chemical reaction model.

[0016] As a preferred embodiment, for the turbulent model in Step SS4, the standard k-ε model is used for calculation:

[0017]

[0018] where ρ is the fluid density, u is the flow velocity, p is the pressure, I is the turbulent intensity, K is the viscous stress, F is the body force, μ is the dynamic viscosity of the fluid, μT is the turbulent kinematic viscosity, is the Lagrangian operator, k is the turbulent kinetic energy, and ∈ is the turbulent dissipation rate.

[0019] As a preferred embodiment, the establishment process of the chemical reaction model in the step SS4 includes:

[0020] Step a: Determine the chemical reaction in the CaCO3 crystallization process:

[0021]

[0022] Step b: Establish an equilibrium reaction thermodynamic database for calculating the component forms of the required species and the numerical simulation of reactive solute transport;

[0023] Step c: Establish the rate equation of the kinetic reaction: Determine the rate equations of the reactions involved in mineral dissolution and precipitation according to the chemical reaction kinetic transition state theory TST.

[0024] As a preferred embodiment, the step b specifically includes: defining the aqueous solution components and the generated species in the process of drain pipe crystallization blockage, determining the generation reaction process and the thermodynamic equilibrium constant of the generated species, and forming a data combination of the aqueous solution components, the generated species and the thermodynamic equilibrium constant, and finally forming an equilibrium reaction thermodynamic database by combining the data combinations of multiple components in the reactive solute transport model.

[0025] As a preferred embodiment, the establishment of the rate equation of the kinetic reaction in the step c specifically includes: adopting the CaCO3 deposition - erosion reaction rate expression:

[0026] m = m d -m r (5)

[0027]

[0028] where m is the net deposition rate, m d is the deposition rate, m r is the erosion rate, β is the convective mass transfer coefficient, k R is the surface reaction rate constant, u is the flow velocity, m f is the fouling mass per unit area, β is the linear expansion coefficient, T w 、T f are the wall temperature and the fluid temperature respectively, d P is the crystal particle size.

[0029] As a preferred embodiment, for the rate equation of the kinetic reaction in the step c, the rate constant k at a temperature of 25 °C is:

[0030] kR = k R0 exp(-E / RT F ) (8)

[0031] where k R and k R0 are the surface reaction rate constants, E is the activation energy, R is the molar gas constant, and T F is the temperature of the scale layer surface.

[0032] As a preferred embodiment, in step SS8, to solve the displacement change of the boundary of the numerical model of the drain pipe crystallization blockage, the moving mesh equation Moving mesh is used for solving, specifically including: performing smoothing processing on the moving boundary:

[0033]

[0034] v mbs = δ mbs |v0|hH (10)

[0035]

[0036] where v0 is the specified normal grid velocity, v mbs is the grid smoothing velocity, δ mbs is the moving boundary smoothing adjustment parameter, h is the grid cell size in m; H is the average surface curvature in 1 / m; is the surface gradient operator.

[0037] The present invention also proposes a numerical simulation system for turbulent chemical crystallization coupling in pipes based on moving meshes, including:

[0038] A model parameter determination module for performing: determining the model parameters of each physical field, where the model parameters include: the fluid density, flow velocity, fluid viscosity, turbulent kinetic energy, turbulent dissipation rate of the turbulent k-ε model, the convective mass transfer coefficient, surface reaction rate constant, activation energy, saturation concentration of the chemical reaction model, the normal grid velocity, fluid velocity, moving boundary smoothing adjustment parameter, surface gradient operator of the moving mesh equation;

[0039] A reactive solute transport equation establishment module for performing: based on the model parameters collected by the model parameter determination module, establishing a reactive solute transport equation in the drain pipe based on the principles of mass and energy conservation and the turbulent equation;

[0040] A primary dissection and discretization module for performing: determining the initial conditions, boundary conditions, hydraulic parameters, source and sink terms of the reactive solute transport model, and performing spatial grid dissection and time discretization;

[0041] A vector concentration distribution module for performing: solving a reactive solute transport model to obtain the distributions of flow velocity vectors and solute concentrations in time and space within the simulation area;

[0042] A clogging numerical model establishment module for performing: based on the results of the reactive solute transport model obtained by the vector concentration distribution module, establishing a numerical model for crystal clogging of a karst tunnel drainage pipe based on a moving mesh according to the moving mesh equation;

[0043] A secondary meshing and discretization module for performing: determining the initial conditions, boundary conditions, model parameters, and source-sink terms of the numerical model for crystal clogging of the drainage pipe in the clogging numerical model establishment module, and performing spatial mesh partitioning and time discretization;

[0044] A clogging numerical model solving module for performing: solving the numerical model for crystal clogging of a karst tunnel drainage pipe to obtain the distributions of flow velocity vectors, solute concentrations, and the volume fraction distribution of the generated crystal substances in time and space within the corrected simulation area;

[0045] A sediment interface change trend module, specifically performing: depicting the displacement change of the boundary of the numerical model for crystal clogging of the drainage pipe based on the changes in the flow field, concentration field, and crystal volume fraction, and completing the numerical simulation of crystal clogging in the karst tunnel.

[0046] As a preferred embodiment, the CFD module, chemical reaction module, and moving mesh module in the simulation software COMSOL are used in the vector concentration distribution module and the clogging numerical model solving module for solving.

[0047] The beneficial effects achieved by the present invention: The numerical simulation method for coupling pipe turbulent flow and chemical crystallization based on a moving mesh of the present invention can realize the coupling process of hydrodynamic-chemical reactions of crystal clogging in karst tunnel drainage pipes, improve the numerical simulation ability of reactive transport in drainage pipes, realize the precise control and dynamic regulation of the crystal clogging process in drainage pipes, and provide technical support for the sustainable utilization of karst tunnel drainage systems and the early identification and safety evaluation of karst tunnel blockages. Description of the Drawings

[0048] Figure 1 is a flow chart of the numerical simulation method for crystal clogging of a karst tunnel drainage pipe;

[0049] Figure 2 is a three-dimensional schematic diagram of the conceptual model of a karst tunnel drainage pipe;

[0050] Figure 3 is a cross-sectional schematic diagram of the conceptual model of a karst tunnel drainage pipe;

[0051] Figure 4 is a distribution diagram of the flow field inside the drainage pipe;

[0052] Figure 5 It is the distribution diagram of CaCO3 concentration field in the drain pipe;

[0053] Figure 6 It is the curve diagram of the change of CaCO3 deposition / erosion rate;

[0054] Figure 7 It is the change result of CaCO3 crystallization rate under different temperature conditions;

[0055] Figure 8 It is the change result of CaCO3 crystallization rate under different flow velocity conditions;

[0056] Figure 9 It is the change result of CaCO3 crystallization rate under different concentration conditions. Specific implementation mode

[0057] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0058] Embodiment 1: The present invention also proposes a numerical simulation system for turbulent chemical crystallization coupling in pipelines based on dynamic meshes, including:

[0059] A model parameter determination module for performing: determining the model parameters of each physical field, where the model parameters include: fluid density, flow velocity, fluid viscosity, turbulent kinetic energy, turbulent dissipation rate of the turbulent k-ε model, convective mass transfer coefficient, surface reaction rate constant, activation energy, saturation concentration of the chemical reaction model, normal phase grid velocity, fluid velocity, moving boundary smoothing adjustment parameter, surface gradient operator of the dynamic mesh equation;

[0060] A reactive solute transport equation establishment module for performing: based on the model parameters collected by the model parameter determination module, establishing a reactive solute transport equation in the drain pipe based on the principles of mass and energy conservation and the turbulent equation;

[0061] A primary mesh discretization module for performing: determining the initial conditions, boundary conditions, hydraulic parameters, source-sink terms of the reactive solute transport model, and performing spatial mesh discretization and time discretization;

[0062] A vector concentration distribution module for performing: solving the reactive solute transport model to obtain the distribution of flow velocity vectors and solute concentrations in time and space in the simulation area;

[0063] A clogging numerical model establishment module for performing: based on the results of the reactive solute transport model obtained by the vector concentration distribution module, establishing a numerical model for karst tunnel drain pipe crystallization clogging based on the dynamic mesh equation;

[0064] The secondary dissection and discretization module is used to perform: determining the initial conditions, boundary conditions, model parameters, and source-sink terms of the drain pipe crystallization clogging numerical model in the clogging numerical model establishment module, and performing spatial grid dissection and time discretization;

[0065] The clogging numerical model solving module is used to perform: solving the karst tunnel drain pipe crystallization clogging numerical model to obtain the distribution of the velocity vector in time and space, the distribution of the solute concentration, and the volume fraction distribution of the generated crystalline substances in the simulation area after correction;

[0066] The sediment interface change trend module specifically performs: depicting the displacement change of the boundary of the drain pipe crystallization clogging numerical model according to the changes of the flow field, concentration field, and crystalline object volume fraction, and completing the numerical simulation of karst tunnel crystallization clogging.

[0067] As a preferred embodiment, the vector concentration distribution module and the clogging numerical model solving module use the CFD module, chemical reaction module, and dynamic mesh module in the simulation software COMSOL to solve.

[0068] Embodiment 2: The present invention provides a numerical simulation method for turbulent chemical crystallization coupling in pipes based on dynamic meshes. The embodiment of the present invention takes the established ideal model of karst tunnel drainage pipes as an example.

[0069] 1) Conceptual model of karst tunnel drain pipe

[0070] According to the indoor test design in the literature research, a conceptual model of the drain pipe with the same physical parameters and hydraulic characteristics as the actual scenario is established. As Figure 2 shown, the model is in a "T" shape. The longer section is the longitudinal pipe, and the shorter section is the transverse pipe. The left end of the longitudinal pipe is the inflow boundary, the right end is the outflow boundary, and the outlet of the transverse pipe is the outflow boundary. The main physical parameters are shown in Table 1. The length of the drainage pipe is 0.3 m, and the pipe diameter is 0.02 m. It is set that the left side of the longitudinal pipe is the given velocity inflow boundary, and the right side of the longitudinal pipe and the outlet of the transverse pipe are free outflow boundaries. In addition, the left side boundary of the longitudinal pipe is the given concentration boundary, and the right side of the longitudinal pipe and the outlet of the transverse pipe are free outflow boundaries. Other hydrodynamic and hydrochemical parameters in the model are shown in Table 2. The simulation duration is 100 d, and the time discretization is set with a given time step Δt = 1 d. The chemical components during the simulation include H2O, Ca 2+ , Mg 2+ , H + ,, HCO - 3, CO3 2- and related aqueous complexes. The mineral components are mainly calcite, dolomite, quartz, albite, orthoclase, muscovite, etc.

[0071] Table 1 Main physical parameters of the conceptual model in the invention embodiment

[0072]

[0073] Table 2 Hydrodynamic and Hydrochemical Parameters of Drainage Pipe

[0074]

[0075] 2) Chemical Reaction System during Crystallization Blockage

[0076] When high-concentration karst groundwater flows into the drainage pipe, Ca 2+ , Mg 2+ , CO3 2- , HCO3 - , CO2, H2O and other ions jointly participate in the reaction process in the system, mainly involving the dissolution-precipitation process of CaCO3.

[0077] The dissolution and precipitation of minerals controlled by thermodynamic equilibrium are judged by the mineral saturation index (SI). The SI is expressed by the following formula:

[0078]

[0079] Among them, SI is the saturation index, IAP is the ion activity product, and K sp is the solubility product constant. If SI < 0, it means the mineral is not saturated; if SI = 0, it means the mineral is not saturated; if SI > 0, it means the mineral has precipitated

[0080] The dissolution and precipitation of minerals controlled by reaction kinetics are represented by the mineral reaction rate. The calculation parameters of the mineral composition and the mineral reaction kinetics rate in the model are shown in Table 3.

[0081] Table 3 Calculation Parameters of Mineral Reaction Kinetics Rate

[0082]

[0083] Note: The superscripts a and b represent the dissolution of minerals under the action of neutral mechanism (spontaneous) and acidic mechanism respectively.

[0084] 3) Determine the Control Equation

[0085] A) The standard k-ε turbulence model is used to calculate the flow field, and the form of the control equation is:

[0086]

[0087]

[0088] Among them, ρ is the fluid density, u is the flow velocity, p is the pressure, I is the turbulence intensity, K is the viscous stress, F is the volume force, μ is the fluid dynamic viscosity, μ Tis the turbulent kinematic viscosity, is the Lagrangian operator, k is the turbulent kinetic energy, and ∈ is the turbulent dissipation rate.

[0089] In the formula, ρ is the fluid density, u is the flow velocity, p is the pressure, I is the turbulence intensity, K is the viscous stress, F is the body force, μ is the dynamic viscosity of the fluid, μ T is the turbulent kinematic viscosity, is the Lagrangian operator, k is the turbulent kinetic energy, and ∈ is the turbulent dissipation rate.

[0090] B) The concentration field is solved using the standard convection-dispersion equation, and the form of the governing equation is:

[0091]

[0092] In the formula, J j is the diffusion flux, c j is the concentration at node j, u is the flow velocity, R j is the source-sink term, D j is the diffusion coefficient.

[0093] C) The chemical reaction field is solved using the net deposition rate (i.e., deposition rate minus erosion rate) model proposed by Kern and Seaton.

[0094] m = m d - m r (7)

[0095] a) The ion diffusion model proposed by Hasson et al. is adopted:

[0096]

[0097] k R = k R0 exp(-E / RT F ) (9)

[0098] In the formula, m d is the deposition rate, β is the convective mass transfer coefficient, k R , k R0 are the surface reaction rate constants, c f , c s are the concentration of CaCO3 in the pipe and the saturation concentration of CaCO3 respectively, E is the activation energy, R is the molar gas constant, T F is the temperature of the scale layer surface.

[0099] b) The model proposed by Bohnet is adopted:

[0100]

[0101] In the formula, m ris the erosion rate, u is the flow velocity, and m f is the fouling mass per unit area, β is the linear expansion coefficient, and T w and T f are the pipe wall temperature and the fluid temperature respectively, and d P is the crystal particle size.

[0102] 4) Establish the dynamic mesh equation

[0103] Based on the dynamic mesh method, the boundary movement speed is specified through a user-defined UDF to describe the displacement change of the moving boundary. Since the boundary will move and deform, the moving boundary smoothing process is required:

[0104]

[0105] v mbs = δ mbs |v0|hH (12)

[0106]

[0107] where v0 is the specified normal grid velocity, v mbs is the grid smoothing velocity, δ mbs is the moving boundary smoothing adjustment parameter, h is the grid cell size (unit: m), H is the average surface curvature (unit: 1 / m), is the surface gradient operator.

[0108] 5) Analysis of the simulation results of the crystallization blockage of the drain pipe in the karst tunnel

[0109] Figure 3 and Figure 4 show the flow field distribution map and the CaCO3 concentration field distribution map in the drain pipe at the end of 100d obtained by solving under the set working conditions respectively. Analysis Figure 3 and Figure 4 shows that the flow velocity in the drain pipe calculated by the model gradually decreases from the inlet section to the outlet section, while the concentration of generated CaCO3 gradually increases from the inlet section to the outlet section. When the flow velocity is small, the erosion rate is also small. At the same time, the larger the amount of CaCO3 generated, the larger the deposition rate. Compared with the inlet section, the net deposition rate m at the outlet section under low flow velocity and high concentration conditions is larger, that is, the crystallization blockage situation at the outlet section is more serious. And compared with the vertical pipe, due to the sharp change in the water flow direction in the horizontal pipe, the flow pattern changes violently and the kinetic energy loss is greater. Therefore, the flow velocity in the horizontal pipe is less than that in the vertical pipe. And according to Figure 4 it can be known that the concentration of generated CaCO3 in the horizontal pipe is greater than that in the vertical pipe at the same time. Similarly, it can be known that the net deposition rate in the horizontal pipe is larger, that is, the blockage situation in the horizontal pipe is more serious than that in the vertical pipe. This result is consistent with the on-site investigation results, further proving the reliability of the established numerical model.

[0110] Figure 5 is the distribution diagram of CaCO3 concentration field in the drain pipe; Figure 6 is the change curve of CaCO3 deposition / erosion rate; It can be seen from Figure 5 and Figure 6 that as the CaCO3 crystallization process continues, the deposition rate decreases slightly but the change range is not large; while the erosion rate has changed significantly. At the initial stage of the crystallization process, the erosion rate increases from almost 0 to 2×10 -7 kg / (m 2 ·s) in a short time, with a large change range, and then maintains a relatively stable growth. At the initial stage, with the formation of the crystallization layer, the effective flow area of the pipeline decreases, resulting in an increase in the flow velocity, and the shear force of the fluid on the crystallization layer increases, so the erosion rate gradually increases. When the CaCO3 crystal grains begin to adhere to the inner wall of the pipeline, their crystal grain size is still small, and the adhesion force with the pipe wall is relatively weak, and it is easily knocked off by water molecules and separated from the wall surface. Only when the crystal grain size is large, the adhesion force between the crystal grains and the wall surface can be stably adsorbed on the wall surface. Although the erosion rate gradually increases during this stage, it can be seen from Figure 5 that it is always less than the deposition rate of CaCO3. According to the net deposition rate calculation formula, it can be known that although the net deposition rate gradually decreases, it is always positive, indicating that within 0 - 100 d, the crystallization deposition process in the drain pipe is continuously proceeding, and a large amount of CaCO3 generated in the fluid crystallizes and precipitates. From the change curve of the deposition rate and the erosion rate, it can be speculated that when the time scale is long enough, if the drain pipe is not completely blocked at the end of the stress period, the deposition rate and the erosion rate will tend to be equal, at which time the net deposition rate is 0, and the CaCO3 crystallization process no longer occurs in the pipeline, and the blockage degree of the drain pipe reaches the maximum value.

[0111] Figure 7 –9 is the change trend diagram of the crystallization rate when changing the temperature, inlet flow rate and inflow concentration. It can be seen from the figure that when changing the temperature, inlet flow rate and ion inflow concentration, the crystallization rate of CaCO -3 will change significantly. When the temperature increases from 283.15K to 303.15K, the value of the CaCO3 crystallization rate after the change amplitude stabilizes increases from almost 0 to 5×10 -7 kg / (m 2 ·s), indicating that the crystallization rate of CaCO3 in the drain pipe is positively correlated with the temperature; when the inlet flow rate increases from 0.5m / s to 0.9m / s, the value of the crystallization rate after the change amplitude stabilizes increases from 2.0×10 -7 kg / (m 2·s) is reduced to a negative value, indicating that the CaCO3 crystallization rate is negatively correlated with the inlet flow rate (it should be noted that the negative value here is a theoretical value. In fact, when the crystallization rate is equal to 0, the deposition rate is equal to the erosion rate, and crystallization no longer occurs at this time); when the ion inflow concentration increases from 6.5 mol / m 3 to 8.5 mol / m 3 , the CaCO3 crystallization rate value after the change amplitude becomes stable increases from nearly 0 to 2.0×10 -7 kg / (m 2 ·s), indicating that the CaCO3 crystallization rate is positively correlated with the ion inflow concentration. It shows that in the actual prevention and control of tunnel drainage system blockage, controlling temperature, flow rate and concentration plays an important role in the prevention and control effect.

[0112] The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and deformations can be made, and these improvements and deformations should also be regarded as the protection scope of the present invention.

Claims

1. A numerical simulation method for coupling turbulent flow and chemical crystallization in pipelines based on dynamic meshes, characterized in that, It includes the following steps: Step SS1: Determine the model parameters of each physical field. The model parameters include: fluid density, flow velocity, fluid viscosity, turbulent kinetic energy, and turbulent dissipation rate of the turbulent k-ε model; convective mass transfer coefficient, surface reaction rate constant, activation energy, and saturation concentration of the chemical reaction model; normal grid velocity, fluid velocity, moving boundary smoothing adjustment parameter, and surface gradient operator of the dynamic grid equation; Step SS2: Based on the model parameters collected in Step SS1, establish a reactive solute transport equation in the drainage pipe based on the principles of mass and energy conservation and the turbulent equation; Step SS3: Determine the initial conditions, boundary conditions, hydraulic parameters, and source-sink terms of the reactive solute transport model, and perform spatial grid discretization and time discretization; Step SS4: Solve the reactive solute transport model to obtain the distributions of the flow velocity vector and solute concentration in time and space in the simulation area; Step SS5: Based on the results of the reactive solute transport model obtained in Step SS4, establish a numerical model for crystal blockage in the karst tunnel drainage pipe based on the dynamic grid according to the dynamic grid equation; Step SS6: Determine the initial conditions, boundary conditions, model parameters, and source-sink terms of the drainage pipe crystal blockage numerical model in Step SS5, and perform spatial grid discretization and time discretization; Step SS7: Solve the numerical model for crystal blockage in the karst tunnel drainage pipe to obtain the distributions of the flow velocity vector, solute concentration, and volume fraction of the generated crystal in time and space in the corrected simulation area; Step SS8: Depict the displacement change of the boundary of the drainage pipe crystal blockage numerical model according to the changes in the flow field, concentration field, and crystal volume fraction to complete the numerical simulation of crystal blockage in the karst tunnel. To solve the displacement change of the boundary of the drainage pipe crystal blockage numerical model in Step SS8, the dynamic grid equation Moving mesh is used for solution, which specifically includes: performing smoothing processing of the moving boundary; v mbs = δ mbs |v0|hH (10) Among them, v0 is the specified normal grid velocity, and v mbs is the grid smoothing velocity, and δ mbs is the smoothing adjustment parameter for the moving boundary, h is the grid cell size in m; H is the average surface curvature in 1 / m; is the surface gradient operator.

2. The numerical simulation method for coupling turbulent chemical crystallization in pipelines based on dynamic meshes according to claim 1, wherein Both the reactive solute transport model in Step SS4 and the drainage pipe crystal blockage numerical model in Step SS7 include a turbulent model and a chemical reaction model.

3. The numerical simulation method for coupling pipeline turbulent chemical crystallization based on dynamic mesh according to claim 2, characterized in that, For the turbulent model in Step SS4, the standard k-ε model is used for calculation: where ρ is the fluid density, u is the flow velocity, p is the pressure, I is the turbulence intensity, K is the viscous stress, F is the body force, μ is the dynamic viscosity of the fluid, μ T is the turbulent kinematic viscosity, is the Lagrangian operator, k is the turbulent kinetic energy, and ∈ is the turbulent dissipation rate.

4. The numerical simulation method for coupling turbulent chemical crystallization in pipelines based on dynamic mesh according to claim 2, wherein, The establishment process of the chemical reaction model in Step SS4 includes: Step a: Determine the chemical reaction of the CaCO3 crystallization process; Step b: Establish an equilibrium reaction thermodynamic database for calculating the component forms of the required species and participating in the numerical simulation of reactive solute transport; Step c: Establish the rate equation of the kinetic reaction: Determine the reaction rate equations for mineral dissolution and precipitation according to the transition state theory of chemical reaction kinetics TST.

5. The numerical simulation method for coupling turbulent chemical crystallization in pipelines based on dynamic meshes according to claim 4, characterized in that, Step b specifically includes: defining the aqueous solution components and generated species during the drainage pipe crystal blockage process, determining the generation reaction process and thermodynamic equilibrium constant of the generated species, and forming a data combination of the aqueous solution components, generated species, and thermodynamic equilibrium constant. Finally, form an equilibrium reaction thermodynamic database by combining the data combinations of multiple components in the reactive solute transport model.

6. The numerical simulation method for coupling turbulent chemical crystallization in pipelines based on dynamic meshes according to claim 4, characterized in that, The establishment of the rate equation for the kinetic reaction in step c specifically includes: adopting the rate expression of CaCO3 deposition - erosion reaction: m = m d -m r (5) where m is the net deposition rate, m d is the deposition rate, m r is the erosion rate, β is the convective mass transfer coefficient, k R is the surface reaction rate constant, u is the flow velocity, m f is the fouling mass per unit area, β is the linear expansion coefficient, T w and T f are the wall temperature and the fluid temperature respectively, d P is the crystal particle size.

7. The numerical simulation method for coupling turbulent chemical crystallization in pipelines based on dynamic meshes according to claim 6, wherein For the rate equation of the kinetic reaction in step c, the rate constant k at a temperature of 25 °C is: k R = k R0 exp(-E / RT F ) (8) where k R and k R0 are the surface reaction rate constants, E is the activation energy, R is the molar gas constant, and T F is the scale surface temperature.

8. A system for the coupled numerical simulation method of turbulent chemical crystallization in a pipeline with dynamic mesh according to claim 1, characterized in that, Including: A model parameter determination module for performing: determining the model parameters of each physical field, where the model parameters include: the fluid density, flow velocity, fluid viscosity, turbulent kinetic energy, and turbulent dissipation rate of the turbulent k-ε model; the convective mass transfer coefficient, surface reaction rate constant, activation energy, and saturation concentration of the chemical reaction model; the normal grid velocity, fluid velocity, moving boundary smoothing adjustment parameter, and surface gradient operator of the dynamic mesh equation; A reactive solute transport equation establishment module for performing: based on the model parameters collected by the model parameter determination module, establishing a reactive solute transport equation in the drain pipe based on the principles of mass and energy conservation and the turbulent equation; A primary dissection and discretization module for performing: determining the initial conditions, boundary conditions, hydraulic parameters, and source - sink terms of the reactive solute transport model, and performing spatial grid dissection and time discretization; A vector concentration distribution module for performing: solving the reactive solute transport model to obtain the distributions of the velocity vector and solute concentration in time and space in the simulation area; A clogging numerical model establishment module for performing: based on the results of the reactive solute transport model obtained by the vector concentration distribution module, establishing a numerical model for crystal clogging of the karst tunnel drain pipe based on the dynamic mesh equation; A secondary dissection and discretization module for performing: determining the initial conditions, boundary conditions, model parameters, and source - sink terms of the drain pipe crystal clogging numerical model in the clogging numerical model establishment module, and performing spatial grid dissection and time discretization; A clogging numerical model solving module for performing: solving the numerical model for crystal clogging of the karst tunnel drain pipe to obtain the distributions of the velocity vector, solute concentration, and volume fraction of the generated crystal in time and space in the corrected simulation area; A sedimentation interface change trend module, specifically performing: depicting the displacement change of the boundary of the drain pipe crystal clogging numerical model according to the changes in the flow field, concentration field, and crystal volume fraction, and completing the numerical simulation of crystal clogging in the karst tunnel.

9. The numerical simulation system for coupling turbulent chemical crystallization in pipelines based on dynamic meshes according to claim 8, characterized in that, In the vector concentration distribution module and the clogging numerical model solving module, the CFD module, chemical reaction module, and dynamic mesh module in the simulation software COMSOL are used for solving.

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