CN114818038A - Level set-based hydrodynamic-chemical crystallization coupling numerical simulation method and system - Google Patents
Level set-based hydrodynamic-chemical crystallization coupling numerical simulation method and system Download PDFInfo
- Publication number
- CN114818038A CN114818038A CN202111023150.0A CN202111023150A CN114818038A CN 114818038 A CN114818038 A CN 114818038A CN 202111023150 A CN202111023150 A CN 202111023150A CN 114818038 A CN114818038 A CN 114818038A
- Authority
- CN
- China
- Prior art keywords
- model
- blockage
- crystallization
- hydrodynamic
- level set
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000002425 crystallisation Methods 0.000 title claims abstract description 69
- 230000008025 crystallization Effects 0.000 title claims abstract description 69
- 238000000034 method Methods 0.000 title claims abstract description 53
- 238000004088 simulation Methods 0.000 title claims abstract description 50
- 238000010168 coupling process Methods 0.000 title claims abstract description 32
- 230000008878 coupling Effects 0.000 title claims abstract description 29
- 238000005859 coupling reaction Methods 0.000 title claims abstract description 29
- 239000000126 substance Substances 0.000 title claims abstract description 27
- 238000006243 chemical reaction Methods 0.000 claims abstract description 46
- 239000013078 crystal Substances 0.000 claims abstract description 38
- 230000008569 process Effects 0.000 claims abstract description 30
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 12
- 238000006073 displacement reaction Methods 0.000 claims abstract description 6
- 230000008021 deposition Effects 0.000 claims description 29
- 239000012530 fluid Substances 0.000 claims description 28
- 239000013598 vector Substances 0.000 claims description 19
- 229910052500 inorganic mineral Inorganic materials 0.000 claims description 16
- 239000011707 mineral Substances 0.000 claims description 16
- 230000008859 change Effects 0.000 claims description 14
- 239000006185 dispersion Substances 0.000 claims description 13
- 102100036790 Tubulin beta-3 chain Human genes 0.000 claims description 10
- 238000006557 surface reaction Methods 0.000 claims description 10
- 230000004913 activation Effects 0.000 claims description 8
- 238000012546 transfer Methods 0.000 claims description 8
- 238000001556 precipitation Methods 0.000 claims description 7
- 238000004090 dissolution Methods 0.000 claims description 6
- 238000004134 energy conservation Methods 0.000 claims description 5
- 239000007864 aqueous solution Substances 0.000 claims description 4
- 230000005514 two-phase flow Effects 0.000 claims description 3
- 102100036788 Tubulin beta-4A chain Human genes 0.000 claims description 2
- 230000007704 transition Effects 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 abstract description 3
- 230000000903 blocking effect Effects 0.000 abstract description 2
- 238000011156 evaluation Methods 0.000 abstract description 2
- 238000011002 quantification Methods 0.000 abstract description 2
- 235000010755 mineral Nutrition 0.000 description 15
- VTYYLEPIZMXCLO-UHFFFAOYSA-L Calcium carbonate Chemical compound [Ca+2].[O-]C([O-])=O VTYYLEPIZMXCLO-UHFFFAOYSA-L 0.000 description 14
- 229910000019 calcium carbonate Inorganic materials 0.000 description 7
- 235000010216 calcium carbonate Nutrition 0.000 description 7
- 150000002500 ions Chemical class 0.000 description 6
- 238000013508 migration Methods 0.000 description 5
- 230000005012 migration Effects 0.000 description 5
- 230000003628 erosive effect Effects 0.000 description 4
- 239000003673 groundwater Substances 0.000 description 4
- 239000011435 rock Substances 0.000 description 3
- 239000011575 calcium Substances 0.000 description 2
- 230000001276 controlling effect Effects 0.000 description 2
- 230000002596 correlated effect Effects 0.000 description 2
- 238000009792 diffusion process Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000006641 stabilisation Effects 0.000 description 2
- 238000011105 stabilization Methods 0.000 description 2
- 229910021532 Calcite Inorganic materials 0.000 description 1
- KWYUFKZDYYNOTN-UHFFFAOYSA-M Potassium hydroxide Chemical compound [OH-].[K+] KWYUFKZDYYNOTN-UHFFFAOYSA-M 0.000 description 1
- 230000002378 acidificating effect Effects 0.000 description 1
- 229910052656 albite Inorganic materials 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000009412 basement excavation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 229910052791 calcium Inorganic materials 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 238000005137 deposition process Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- YGANSGVIUGARFR-UHFFFAOYSA-N dipotassium dioxosilane oxo(oxoalumanyloxy)alumane oxygen(2-) Chemical compound [O--].[K+].[K+].O=[Si]=O.O=[Al]O[Al]=O YGANSGVIUGARFR-UHFFFAOYSA-N 0.000 description 1
- 229910000514 dolomite Inorganic materials 0.000 description 1
- 239000010459 dolomite Substances 0.000 description 1
- 238000013401 experimental design Methods 0.000 description 1
- 239000010433 feldspar Substances 0.000 description 1
- 230000004907 flux Effects 0.000 description 1
- 230000004941 influx Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 229910052627 muscovite Inorganic materials 0.000 description 1
- 230000007935 neutral effect Effects 0.000 description 1
- 239000011148 porous material Substances 0.000 description 1
- 229940072033 potash Drugs 0.000 description 1
- BWHMMNNQKKPAPP-UHFFFAOYSA-L potassium carbonate Substances [K+].[K+].[O-]C([O-])=O BWHMMNNQKKPAPP-UHFFFAOYSA-L 0.000 description 1
- 235000015320 potassium carbonate Nutrition 0.000 description 1
- 239000010453 quartz Substances 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 238000010008 shearing Methods 0.000 description 1
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 230000002269 spontaneous effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/10—Analysis or design of chemical reactions, syntheses or processes
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Geometry (AREA)
- Computer Hardware Design (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Computational Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Computing Systems (AREA)
- Civil Engineering (AREA)
- Structural Engineering (AREA)
- Algebra (AREA)
- Architecture (AREA)
- Fluid Mechanics (AREA)
- Mathematical Physics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Analytical Chemistry (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Crystallography & Structural Chemistry (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a level set-based hydrodynamic-chemical crystallization coupling numerical simulation method and system, which are used for simulating a karst water crystallization blocking process of a tunnel drainage pipeline in a karst region. The model can break through the parameter limitation of an empirical formula and a numerical quantification method of a traditional DBL theoretical model only considering the limitation of a homogeneous flow system, and tries to establish a multi-field coupling hydrodynamic-chemical reaction coupling model to simulate the process of crystal blockage of a drainage pipeline of a karst tunnel. The method provided by the invention comprises the following steps: a karst water crystallization blockage model of the drainage pipe is constructed in consideration of coupling of a pipeline hydrodynamic field, a concentration field and a chemical reaction field, meanwhile, a process of drainage pipe crystallization blockage under combined action of three factors, namely temperature, ion concentration and flow speed, is considered, and moving boundary displacement is described on the basis of a level set method, so that the karst tunnel drainage pipe crystallization blockage numerical simulation is carried out. The simulation technology provided by the invention can provide technical support for early identification and safety evaluation of the blockage of the karst tunnel.
Description
Technical Field
The invention relates to a hydrodynamic-chemical crystallization coupling numerical simulation method and system based on a level set, and belongs to the technical field of hydrology and water resources.
Background
In recent years, China builds a large number of tunnel projects in karst areas, hydrogeological conditions of the karst areas are complex, water seepage and water burst disasters of tunnels are frequent, and tunnel construction often needs a matched drainage system. At present, various tunnel water-proof and drainage designs in different forms exist in the industry, however, in any form, tunnel excavation changes karst underground water seepage conditions, the phenomenon that a large amount of underground water seepage crystals block drainage pipelines occurs in a tunnel due to changes of pressure release and temperature, tunnel lining and supporting structures are corroded, engineering accidents such as tunnel deformation, water burst and collapse are caused, and maintenance of a tunnel engineering drainage system and tunnel operation safety are seriously influenced.
However, the system research of numerical simulation technology on the prediction and accurate control technology of the tunnel drain pipe crystallization blockage dynamic process is lacked in the actual production process. The key scientific problem of drain pipe crystallization plugging is the study of hydrodynamic characteristics and reactive solute transport processes in the karst system within the drain pipe. The crystallization blocking process is a complex process of coupling fluid migration and chemical reaction among ions in the karst groundwater, and is an extremely complex nonlinear reaction solute migration system, and comprises a seepage dynamic field in rock pores in the karst groundwater seepage process, a dispersion field of solute in a low-permeability heterogeneous medium, water-rock interaction between the karst groundwater and rock minerals and a multi-field coupling process of reactive chemical dynamic fields generated in the dissolving-precipitating process of soluble salt components.
The study on the complex coupling process of fluid migration and geochemical reaction in the crystallization plugging process to further construct a three-dimensional karst tunnel drainage system and the migration of reactive solutes is a key technical means for accurately depicting dissolution-precipitation in the crystallization plugging process and is also the basis for realizing accurate quantification of crystallization plugging.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a hydrodynamic-chemical crystallization coupling numerical simulation method and a hydrodynamic-chemical crystallization coupling numerical simulation system based on a level set.
The invention specifically adopts the following technical scheme: the hydrodynamic-chemical crystallization coupling numerical simulation method based on the level set comprises the following steps:
step SS 1: determining model parameters for each physical field, the model parameters comprising: the fluid density, flow velocity, fluid viscosity, turbulent kinetic energy and turbulent dissipation rate of the turbulent k-epsilon model, the convective mass transfer coefficient, surface reaction rate constant, activation energy and saturation concentration of the chemical reaction model, the level set variable, the fluid velocity, the reinitialization parameter and the interface thickness control parameter of the level set model;
step SS 2: establishing a reactive solute transport equation in the drain pipe based on the basic principle of mass and energy conservation and a turbulence equation according to the model parameters collected in the step SS 1;
step SS 3: determining initial conditions, boundary conditions, hydraulic parameters and source and sink items of a reactive solute transport model, and performing space mesh subdivision and time dispersion;
step SS 4: solving a reactive solute transport model to obtain the distribution of flow velocity vectors and the distribution of solute concentration in time and space in a simulation area;
step SS 5: on the basis of the reactive solute transport model result obtained in the step SS4, establishing a hydrodynamic-chemical crystallization process coupling numerical simulation model based on a level set according to a level set equation;
step SS 6: determining initial conditions, boundary conditions, model parameters and source and sink items of a drain pipe crystallization blockage numerical model, and performing space grid subdivision and time dispersion;
step SS 7: solving a numerical model of crystal blockage of the drainage pipe of the karst tunnel to obtain the distribution of flow velocity vectors and the distribution of solute concentration in time and space in the corrected simulation area and the volume fraction distribution of generated crystals;
step SS 8: and (4) according to the changes of the flow field, the concentration field and the volume fraction of the crystal, describing the change trend of the interface of the deposition layer, and finishing the numerical simulation of the crystal blockage of the karst tunnel.
As a preferred embodiment, the model of the transport of the reactive solute in step SS4 and the numerical model of the crystal blockage of the drain pipe in step SS7 include a model of turbulence and a model of chemical reaction.
As a preferred embodiment, the turbulence model in step SS4 is calculated using a standard k-epsilon model:
wherein 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 hydrodynamic viscosity, μ T In order to achieve a turbulent kinematic viscosity,
for lagrange's operator, k is the turbulent kinetic energy and epsilon is the turbulent dissipation ratio.
As a preferred embodiment, the process of establishing the chemical reaction model in step SS4 includes:
step a: determination of CaCO 3 Chemical reaction in the crystallization process:
step b: establishing an equilibrium reaction thermodynamic database for calculating the component morphology of the required species and participating in reactive solute transport numerical simulation;
step c: establishing a rate equation of the kinetic reaction: and determining a reaction rate equation participating in mineral dissolution and precipitation according to the chemical reaction kinetics transition state theory TST.
As a preferred embodiment, the step b specifically includes: defining the components of an aqueous solution and generating species in the process of drain pipe crystallization blockage, determining the generating reaction process and thermodynamic equilibrium constant of the generating species, combining the components of the aqueous solution, the generating species and the thermodynamic equilibrium constant into a data combination, and finally combining the data of a plurality of components in a reactive solute transport model into an equilibrium reaction thermodynamic database.
As a preferred embodiment, the rate equation for establishing the kinetic reaction in step c specifically includes: using CaCO 3 Deposition-denudation reaction rate expression:
m＝m d -m r (5)
wherein m is the net deposition rate, m d For deposition rate, m r Beta is convective mass transfer coefficient, k is denudation rate R Is the surface reaction rate constant, u is the flow velocity, m f Is the mass of dirt per unit area, beta is the coefficient of linear expansion, T w 、T f Respectively, wall temperature and fluid temperature, d P Is the crystal grain size.
In a preferred embodiment, the rate equation of the kinetic reaction in step c has a rate constant k at 25 ℃ of:
k R ＝k R0 exp(-E/RT F ) (8)
wherein k is R 、k R0 Is the surface reaction rate constant, E is the activation energy, R is the molar gas constant, T F The surface temperature of the scale layer.
As a preferred embodiment, the step SS8 is to solve the displacement variation of the boundary of the numerical model of the crystal plugging of the drainage pipe, and capture the motion of the two-phase flow interface by the level set equation based on the level set method:
where φ is a level set variable, u is a fluid velocity, γ is a reinitialization parameter, and has the unit of m/s, ε is an interface thickness control parameter (unit: m),
is a gradient operator.
The invention also provides a hydrodynamic-chemical crystallization coupling numerical simulation system based on the level set, which comprises:
a model parameter determination module to perform: determining model parameters for each physical field, the model parameters comprising: the fluid density, flow velocity, fluid viscosity, turbulent flow kinetic energy and turbulent flow dissipation rate of the turbulent flow k-epsilon model, the convective mass transfer coefficient, surface reaction rate constant, activation energy and saturation concentration of the chemical reaction model, the normal phase grid speed, the fluid speed and the moving boundary smooth adjustment parameter of the level set equation and the curved surface gradient operator;
a reactive solute transport equation building module to perform: determining model parameters collected by a module according to the model parameters, and establishing a reactive solute transport equation in the drainage pipe based on a mass and energy conservation principle and a turbulence equation;
a primary subdivision discrete module for executing: determining initial conditions, boundary conditions, hydraulic parameters and source and sink items of a reactive solute transport model, and performing space mesh subdivision and time dispersion;
a vector concentration distribution module to perform: solving a reactive solute transport model to obtain the distribution of flow velocity vectors and the distribution of solute concentration in time and space in a simulation area;
a blockage numerical model building module for executing: on the basis of a reactive solute transport model result obtained by a vector concentration distribution module, establishing a hydrodynamic-chemical crystallization process coupling numerical simulation model based on a level set according to a level set equation;
the secondary subdivision discrete module is used for executing: determining initial conditions, boundary conditions, model parameters and source-sink items of a drain pipe crystallization blockage numerical model in the blockage numerical model building module, and performing space grid subdivision and time dispersion;
a blockage numerical model solving module for performing: solving a numerical model of crystal blockage of the drainage pipe of the karst tunnel to obtain the distribution of flow velocity vectors, the distribution of solute concentration and the volume fraction distribution of generated crystals in the corrected simulation area in time and space;
the deposition interface change trend module specifically executes the following steps: and (4) according to the changes of the flow field, the concentration field and the volume fraction of the crystal, describing the displacement change of the boundary of the numerical model for the crystal blockage of the drain pipe, and finishing the numerical simulation of the crystal blockage of the karst tunnel.
As a better embodiment, the vector concentration distribution module and the blockage numerical model solving module adopt a CFD module, a chemical reaction module and a Level Set model Level Set in simulation software COMSOL to solve.
The invention achieves the following beneficial effects: the hydrodynamic-chemical crystallization coupling numerical simulation method and system based on the level set can realize the hydrodynamic-chemical reaction coupling process of the karst tunnel drain pipe crystallization blockage, improve the simulation capability of the drainage pipe reaction migration numerical simulation, realize the accurate control and dynamic regulation of the drainage pipe crystallization blockage process, and provide technical support for the sustainable utilization of the karst tunnel drain system and the early identification and safety evaluation of the karst tunnel blockage.
Drawings
FIG. 1 is a flow chart of a numerical simulation method for crystal plugging of a drainage pipe of a karst tunnel;
FIG. 2 is a schematic perspective view of a conceptual model of a drainage pipe of a karst tunnel;
FIG. 3 is a schematic cross-sectional view of a conceptual model of a drainage pipe of a karst tunnel;
FIG. 4 is a diagram showing the variation of the crystal deposition interface of CaCO3 in the drain pipe;
figure 5 is a graph of CaCO3 deposition/erosion rate change;
FIG. 6 shows the results of the change in the crystallization rate of CaCO3 under different temperature conditions;
FIG. 7 shows the results of the variation of the crystallization rate of CaCO3 at different flow rates;
figure 8 is the result of the change in the crystallization rate of CaCO3 at different concentrations.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
Example 1: the invention provides a hydrodynamic-chemical crystallization coupling numerical simulation system based on a level set, which comprises:
a model parameter determination module to perform: determining model parameters for each physical field, the model parameters comprising: the fluid density, flow velocity, fluid viscosity, turbulent flow kinetic energy and turbulent flow dissipation rate of the turbulent flow k-epsilon model, the convective mass transfer coefficient, surface reaction rate constant, activation energy and saturation concentration of the chemical reaction model, the normal phase grid speed, the fluid speed and the moving boundary smooth adjustment parameter of the level set equation and the curved surface gradient operator;
a reactive solute transport equation building module to perform: determining model parameters collected by a module according to the model parameters, and establishing a reactive solute transport equation in the drainage pipe based on a mass and energy conservation principle and a turbulence equation;
a primary subdivision discrete module for executing: determining initial conditions, boundary conditions, hydraulic parameters and source and sink items of a reactive solute transport model, and performing space mesh subdivision and time dispersion;
a vector concentration distribution module to perform: solving a reactive solute transport model to obtain the distribution of flow velocity vectors and the distribution of solute concentration in time and space in a simulation area;
a blockage numerical model building module for executing: on the basis of a reactive solute transport model result obtained by a vector concentration distribution module, establishing a hydrodynamic-chemical crystallization process coupling numerical simulation model based on a level set according to a level set equation;
the secondary subdivision discrete module is used for executing: determining initial conditions, boundary conditions, model parameters and source-sink items of a drain pipe crystallization blockage numerical model in the blockage numerical model building module, and performing space grid subdivision and time dispersion;
a blockage numerical model solving module for performing: solving a numerical model of crystal blockage of the drainage pipe of the karst tunnel to obtain the distribution of flow velocity vectors, the distribution of solute concentration and the volume fraction distribution of generated crystals in the corrected simulation area in time and space;
the deposition interface change trend module specifically executes the following steps: and (4) according to the changes of the flow field, the concentration field and the volume fraction of the crystal, describing the displacement change of the boundary of the numerical model for the crystal blockage of the drain pipe, and finishing the numerical simulation of the crystal blockage of the karst tunnel.
As a better embodiment, the vector concentration distribution module and the blockage numerical model solving module adopt a CFD module, a chemical reaction module and a Level Set model Level Set in simulation software COMSOL to solve.
Example 2: the invention provides a hydrodynamic-chemical crystallization coupling numerical simulation system based on a level set.
1) Conceptual model of karst tunnel drain pipe
According to the indoor experimental design in literature research, a drain pipe conceptual model with the same physical parameters and hydraulic characteristics as those under the actual situation is established. As shown in fig. 2, the left end is an inflow boundary and the right end is an outflow boundary. The main physical parameters are shown in Table 1, the length of the drainage pipeline is 0.3m, and the diameter of the pipeline is 0.02 m. The left side is set to the inflow boundary for a given flow rate and the right side is set to the free outflow boundary. Furthermore, the left boundary is a given concentration boundary and the right is a free-flow boundary. Other hydrodynamic and water chemistry parameters in the model are shown in table 2. The analog duration is 100d, and the time dispersion is set with a given time step Δ t equal to 1 d. The chemical component in the simulation process comprises H 2 O、Ca 2+ 、Mg 2+ 、H + 、
CO 3 2- And related water phase complex, wherein the mineral components mainly comprise calcite, dolomite, quartz, albite, potash feldspar, muscovite, etc.
TABLE 1 main physical parameters of conceptual model in the inventive example
TABLE 2 Drain pipe hydrodynamic and hydrochemical parameters
2) Chemical reaction system in crystallization plugging process
High concentration karst groundwater flows into the drainage pipeline, Ca 2+ 、Mg 2+ 、CO 3 2- 、HCO 3 - 、 CO 2 、H 2 The reaction process in the system in which O plasma participates together mainly relates to CaCO 3 Dissolution-precipitation process of (a).
Controlling dissolution and precipitation of minerals by thermodynamic equilibrium the dissolution or precipitation state of a mineral is judged by the mineral Saturation Index (SI), which is expressed by the following formula:
wherein SI is saturation index, IAP is ion activity product, K sp Is the solubility product constant. If SI<0, indicating that the mineral does not reach saturation; if SI is 0, the mineral is not saturated; if SI>0, indicating that the mineral has precipitated
The mineral dissolution precipitation controlled by the reaction kinetics is expressed by the mineral reaction rate, and the calculated parameters in the model relating to the mineral composition and the mineral reaction kinetics rate are shown in table 3.
TABLE 3 calculated parameters of mineral reaction kinetics rates
Note: the superscripts a, b represent dissolution of the mineral by the neutral mechanism (spontaneous) and by the acidic mechanism, respectively.
3) Determining a governing equation
A) The flow field is calculated by adopting a standard k-epsilon turbulence model, and the form of a control equation is as follows:
wherein 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 hydrodynamic viscosity, μ T In order to achieve a turbulent kinematic viscosity,
for lagrange's operator, k is the turbulent kinetic energy and epsilon is the turbulent dissipation ratio.
B) And (3) solving the concentration field by adopting a standard convection dispersion equation, wherein the control equation is in the form of:
in the formula, J j To diffuse the flux, c j Is the concentration at node j, u is the flow rate, R j As a source or sink item, D j Is the diffusion coefficient.
C) The chemical reaction field was solved using the net deposition rate (i.e., deposition rate minus denudation rate) model proposed by Kern and Seaton.
m＝m d -m r (7)
a) The ion diffusion model proposed by Hasson et al was used:
k R ＝k R0 exp(-E/RT F ) (9)
in the formula m d For deposition rate, β is convective mass transfer coefficient, k R 、k R0 Is a surface reaction rate constant, c f 、c s Respectively being CaCO in tubes 3 Concentration and CaCO 3 E is activation energy, R is molar gas constant, T F The surface temperature of the scale layer.
b) Using the model proposed by Bohnet:
in the formula m r For the denudation rate, u is the flow velocity, m f Is the mass of dirt per unit area, beta is the coefficient of linear expansion, T w 、T f Respectively, wall temperature and fluid temperature, d P Is the crystal grain size.
4) Establishing a level set model
Capturing the motion of the two-phase flow interface by a level set equation based on a level set method:
where φ is the level set variable, u is the fluid velocity, γ is the reinitialization parameter (unit: m/s), ε is the interface thickness control parameter (unit: m),
is a gradient operator.
5) Analysis of simulation result of crystal blockage of karst tunnel drain pipe
FIG. 3 shows CaCO in the tunnel drain pipe 3 Graph of the deposition interface of the crystalline layer as a function of time, of the deposition interface of the calcium carbonate crystalsThe change is consistent with the change of the calcium carbonate concentration field, CaCO 3 The greater the concentration, the faster the crystalline deposition rate. From 0d to 100d, the thickness of the crystallization layer attached to the tube wall gradually increases as the crystallization process continues, and it can be seen from fig. 6 that the deposition interface shows obviously uneven variation, and at the same time, the thickness of the deposition layer at the outlet section is larger than that at the inlet section.
FIG. 4 and FIG. 5 are CaCO 3 Deposition, denudation and net deposition rate as a function of time (0-100 d). As can be seen from FIG. 4, with CaCO 3 The crystallization process is continuously carried out, the deposition rate is reduced to a certain extent, but the variation amplitude is not large; whereas the rate of degradation changes more significantly. At the beginning of the crystallization process, the denudation rate increases from nearly 0 to 2X 10 in a short time -7 kg/(m 2 S) with a larger amplitude of change, and then maintains a more stable growth. In the early stage, as the crystallization layer is generated, the effective flow area of the pipeline is reduced, so that the flow velocity begins to increase, the shearing force of the fluid on the crystallization layer is enhanced, and the denudation rate is gradually increased. And CaCO 3 When the crystal grains begin to be attached to the inner wall of the pipeline, the crystal grains have smaller sizes and weaker adhesion with the pipeline wall, and are easy to be knocked by water molecules to be separated from the wall surface, and only when the crystal grains have larger sizes, the adhesion between the crystal grains and the wall surface can be stably attached to the wall surface. Although the denudation rate is gradually increased at this stage, it is always smaller than CaCO as can be seen from FIG. 5 3 The deposition rate of (2) is known from the net deposition rate calculation formula, the net deposition rate is always positive although gradually reduced, which means that the crystallization deposition process in the drain pipeline is continuously carried out within 0-100d, and CaCO generated in the fluid 3 A large amount of crystals are precipitated. From the plot of the deposition rate versus 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, and at this time, the net deposition rate is 0, and no CaCO will occur in the pipe 3 The clogging degree of the drain pipe reaches a maximum value in the crystallization process.
FIGS. 6-8 are graphs showing the trend of crystallization rate with varying temperature, inlet flow rate and influent concentration. It can be seen from the figure thatCaCO when changing the temperature, the inlet flow rate and the ion inflow concentration 3 The crystallization rate of (a) is significantly changed. CaCO after amplitude stabilization when the temperature is increased from 283.15K to 303.15K 3 The crystallization rate increases from almost 0 to 5X 10 -7 kg/(m 2 S) indicating CaCO in the drainage pipeline 3 The crystallization rate of (a) is positively correlated with temperature; when the inlet flow velocity is increased from 0.5m/s to 0.9m/s, the value of the crystallization velocity after amplitude stabilization is from 2.0 multiplied by 10 -7 kg/(m 2 S) decrease to a negative value, indicating CaCO 3 The crystallization rate is inversely related to the inlet flow rate (note that, here, a negative value is a theoretical value, and in fact, when the crystallization rate is equal to 0, the deposition rate is equal to the erosion rate, and no crystallization occurs); when the ion inflow concentration is from 6.5mol/m 3 Increased to 8.5mol/m 3 CaCO with stabilized amplitude 3 The crystallization rate value increases from almost 0 to 2.0X 10 -7 kg/(m 2 S) indicating CaCO 3 The crystallization rate is positively correlated with the ion influx concentration. The method shows that in the actual blockage prevention and control of the tunnel drainage system, the prevention and control effect is played an important role by controlling the temperature, the flow rate and the concentration.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. The hydrodynamic-chemical crystallization coupling numerical simulation method based on the level set is characterized by comprising the following steps of:
step SS 1: determining model parameters for each physical field, the model parameters comprising: the fluid density, flow velocity, fluid viscosity, turbulent kinetic energy and turbulent dissipation rate of the turbulent k-epsilon model, the convective mass transfer coefficient, surface reaction rate constant, activation energy and saturation concentration of the chemical reaction model, the level set variable, the fluid velocity, the reinitialization parameter and the interface thickness control parameter of the level set model;
step SS 2: establishing a reactive solute transport equation in the drain pipe based on the basic principle of mass and energy conservation and a turbulence equation according to the model parameters collected in the step SS 1;
step SS 3: determining initial conditions, boundary conditions, hydraulic parameters and source and sink items of a reactive solute transport model, and performing space mesh subdivision and time dispersion;
step SS 4: solving a reactive solute transport model to obtain the distribution of flow velocity vectors and the distribution of solute concentration in time and space in a simulation area;
step SS 5: on the basis of the reactive solute transport model result obtained in the step SS4, establishing a hydrodynamic-chemical crystallization process coupling numerical simulation model based on a level set according to a level set equation;
step SS 6: determining initial conditions, boundary conditions, model parameters and source and sink items of a drain pipe crystallization blockage numerical model, and performing space grid subdivision and time dispersion;
step SS 7: solving a numerical model of crystal blockage of the drainage pipe of the karst tunnel to obtain the distribution of flow velocity vectors and the distribution of solute concentration in time and space in the corrected simulation area and the volume fraction distribution of generated crystals;
step SS 8: and (4) according to the changes of the flow field, the concentration field and the volume fraction of the crystal, describing the change trend of the interface of the deposition layer, and finishing the numerical simulation of the crystal blockage of the karst tunnel.
2. The level-set based hydrodynamic-chemical crystallization coupling numerical simulation method according to claim 1, wherein the reactive solute transport model in step SS4 and the drain pipe crystallization blockage numerical model in step SS7 each comprise a turbulence model and a chemical reaction model.
3. The level-set based hydrodynamic-chemical crystallographic coupling numerical simulation method of claim 2, wherein the turbulence model in step SS4 is calculated using a standard k-epsilon model:
wherein 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 hydrodynamic viscosity, μ T In order to achieve a turbulent kinematic viscosity,
for lagrange's operator, k is the turbulent kinetic energy and epsilon is the turbulent dissipation ratio.
4. The level-set based hydrodynamic-chemical crystallization coupling numerical simulation method according to claim 2, wherein the establishing process of the chemical reaction model in the step SS4 comprises:
step a: determination of CaCO 3 Chemical reaction in the crystallization process:
step b: establishing an equilibrium reaction thermodynamic database for calculating the component morphology of the required species and participating in reactive solute transport numerical simulation;
step c: establishing a rate equation of the kinetic reaction: and determining a reaction rate equation participating in mineral dissolution and precipitation according to the chemical reaction kinetics transition state theory TST.
5. The level set-based hydrodynamic-chemical crystallization coupling numerical simulation method according to claim 4, wherein the step b specifically comprises: defining the components of an aqueous solution and generating species in the process of drain pipe crystallization blockage, determining the generating reaction process and thermodynamic equilibrium constant of the generating species, combining the components of the aqueous solution, the generating species and the thermodynamic equilibrium constant into a data combination, and finally combining the data of a plurality of components in a reactive solute transport model into an equilibrium reaction thermodynamic database.
6. The level-set based hydrodynamic-chemical crystallization coupling numerical simulation method according to claim 4, wherein the rate equation for establishing the kinetic reaction in step c specifically comprises: using CaCO 3 Deposition-denudation reaction rate expression:
m＝m d -m r (5)
wherein m is the net deposition rate, m d For deposition rate, m r Beta is convective mass transfer coefficient, k is denudation rate R Is the surface reaction rate constant, u is the flow velocity, m f Is the mass of dirt per unit area, beta is the coefficient of linear expansion, T w 、T f Respectively, wall temperature and fluid temperature, d P Is the crystal grain size.
7. The level-set based hydrodynamic-chemical crystallization coupling numerical simulation method according to claim 6, wherein the rate equation of the kinetic reaction in the step c has a rate constant k at 25 ℃ of:
k R ＝k R0 exp(-E/RT F ) (8)
wherein k is R 、k R0 Is the surface reaction rate constant, E is the activation energy, R is the molar gas constant, T F The surface temperature of the scale layer.
8. The level-set based hydrodynamic-chemical crystallization coupling numerical simulation method according to claim 1, wherein the step SS8 is implemented by solving the displacement variation of the boundary of the numerical model of the crystallization clogging of the water discharge pipe, and the motion of the two-phase flow interface is captured by a level-set equation based on the level-set method:
where φ is a level set variable, u is a fluid velocity, γ is a reinitialization parameter, and has the unit of m/s, ε is an interface thickness control parameter (unit: m),
is a gradient operator.
9. Hydrodynamic-chemical crystallization coupling numerical simulation system based on level set, which is characterized by comprising:
a model parameter determination module to perform: determining model parameters for each physical field, the model parameters comprising: the fluid density, flow velocity, fluid viscosity, turbulent flow kinetic energy and turbulent flow dissipation rate of the turbulent flow k-epsilon model, the convective mass transfer coefficient, surface reaction rate constant, activation energy and saturation concentration of the chemical reaction model, the normal phase grid speed, the fluid speed and the moving boundary smooth adjustment parameter of the level set equation and the curved surface gradient operator;
a reactive solute transport equation building module to perform: determining model parameters collected by a module according to the model parameters, and establishing a reactive solute transport equation in the drainage pipe based on a mass and energy conservation principle and a turbulence equation;
a primary subdivision discrete module for executing: determining initial conditions, boundary conditions, hydraulic parameters and source and sink items of a reactive solute transport model, and performing space mesh subdivision and time dispersion;
a vector concentration distribution module to perform: solving a reactive solute transport model to obtain the distribution of flow velocity vectors and the distribution of solute concentration in time and space in a simulation area;
a blockage numerical model building module for executing: on the basis of a reactive solute transport model result obtained by a vector concentration distribution module, establishing a hydrodynamic-chemical crystallization process coupling numerical simulation model based on a level set according to a level set equation;
the secondary subdivision discrete module is used for executing: determining initial conditions, boundary conditions, model parameters and source-sink items of a drain pipe crystallization blockage numerical model in the blockage numerical model building module, and performing space grid subdivision and time dispersion;
a blockage numerical model solving module for performing: solving a numerical model of crystal blockage of the drainage pipe of the karst tunnel to obtain the distribution of flow velocity vectors, the distribution of solute concentration and the volume fraction distribution of generated crystals in the corrected simulation area in time and space;
the deposition interface change trend module specifically executes the following steps: and (4) according to the changes of the flow field, the concentration field and the volume fraction of the crystal, describing the displacement change of the boundary of the numerical model for the crystal blockage of the drain pipe, and finishing the numerical simulation of the crystal blockage of the karst tunnel.
10. The system according to claim 9, wherein the CFD module, the chemical reaction module and the Level Set model Level Set are used in the vector concentration distribution module and the blockage numerical model solving module to solve.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111023150.0A CN114818038A (en) | 2021-09-01 | 2021-09-01 | Level set-based hydrodynamic-chemical crystallization coupling numerical simulation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111023150.0A CN114818038A (en) | 2021-09-01 | 2021-09-01 | Level set-based hydrodynamic-chemical crystallization coupling numerical simulation method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114818038A true CN114818038A (en) | 2022-07-29 |
Family
ID=82525458
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111023150.0A Pending CN114818038A (en) | 2021-09-01 | 2021-09-01 | Level set-based hydrodynamic-chemical crystallization coupling numerical simulation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114818038A (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110147575A (en) * | 2019-04-18 | 2019-08-20 | 河海大学 | A kind of calculation method that the two-phase stream interface based on single layer particle levels collection captures |
| CN113051843A (en) * | 2021-03-10 | 2021-06-29 | 南京大学 | Sandstone-type uranium ore CO2+O2Reaction migration numerical simulation method for in-situ leaching uranium mining |
-
2021
- 2021-09-01 CN CN202111023150.0A patent/CN114818038A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110147575A (en) * | 2019-04-18 | 2019-08-20 | 河海大学 | A kind of calculation method that the two-phase stream interface based on single layer particle levels collection captures |
| CN113051843A (en) * | 2021-03-10 | 2021-06-29 | 南京大学 | Sandstone-type uranium ore CO2+O2Reaction migration numerical simulation method for in-situ leaching uranium mining |
Non-Patent Citations (1)
| Title |
|---|
| 徐中平;周训;崔相飞;拓明明;王昕昀;张颖;: "岩溶区地下水数值模拟研究进展", 中国岩溶, no. 04, 15 August 2018 (2018-08-15) * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110609974B (en) | Acid fracturing fracture dynamic fluid loss calculation method considering wormhole expansion | |
| Haklidir et al. | Fuzzy control of calcium carbonate and silica scales in geothermal systems | |
| Rosarina et al. | Mathematical Design Study of Drainage And Dewatering Strategies: Integrated System For Water Management in Open-Pit Mining | |
| CN114974449A (en) | Pipeline turbulence chemical crystallization coupling numerical simulation method and system based on dynamic grid | |
| CN111101925A (en) | Method for evaluating scaling trend of water injection well | |
| Levin et al. | Mathematical prediction of frozen wall thickness in shaft sinking | |
| US20190275572A1 (en) | Method using artificial freezing technique for sealing and displacement of soil pollutant | |
| Zhangzhong et al. | A kinetic model for the chemical clogging of drip irrigation system using saline water | |
| CN108797533B (en) | Design method of circular drainage hole of debris flow sand dam | |
| Roy et al. | Modeling the formation of efflorescence and subflorescence caused by salt solution evaporation from porous media | |
| Huo et al. | Porosity and permeability variations of a dam curtain during dissolution | |
| Kohfahl et al. | Validity and slopes of the linear equation of state for natural brines in salt lake systems | |
| CN114818038A (en) | Level set-based hydrodynamic-chemical crystallization coupling numerical simulation method and system | |
| EA200400496A1 (en) | METHOD AND SYSTEM FOR PRODUCTION OF OIL AND GAS MIXTURES THROUGH WELL | |
| Wu et al. | Migration and phase change phenomena and characteristics of molten salt leaked into soil porous system | |
| Wang et al. | Improvements in saline soil and the law of water-salt transport based on salt inhibition using MICP technology | |
| Dontsov et al. | Dilution and hydrate forming process in shock waves | |
| CN110990753B (en) | Method for calculating leaching effect of concealed pipe system | |
| Liu et al. | A comparative study on hydrodynamics and hydrochemistry coupled simulations of drainage pipe crystallization blockage in karst tunnels | |
| CN103523889A (en) | PRB joint control-based hydraulic power capturing method for removing contaminants in underground water | |
| CN116796655A (en) | Method for quantitatively predicting dynamic scaling thickness of water injection shaft | |
| Liu et al. | Modeling changes in permeability characteristics of gypsified rocks accompanying brine flow | |
| De Graaff et al. | Neutralization of sulphuric acid by percolation through limestone | |
| CN111125863B (en) | Hydraulic punching pulping proportioning method for mucky soil | |
| CN204142596U (en) | A kind of experimental provision of simulating Limestone pavement tunneling drain calcium carbonate crystal rule |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |