Numerical simulation method of hydrothermal plume motion characteristics based on Fluent software

Abstract

The present invention relates to a numerical simulation method of the motion characteristics of hydrothermal plumes based on Fluent software. Specifically: 1. Construct a custom function; 2. Establish a dynamic model; 3. Divide the grid; 4. Numerical solution to determine the maximum rise height of the plume and the calculation formula of the neutral buoyancy layer height; 5. Output the solution result. The present invention can simulate the changes in various parameters of the hydrothermal plume, which is helpful to understand the material transport and energy cycle of the ocean; at the same time, compared with traditional deep-sea in-situ measurements, it has the advantages of low cost and complete data. The results show that under the same working conditions, the maximum rise height and the neutral buoyancy layer height of the simulation results compared with the measured results are basically consistent, and the error is less than 5%.

Description

Technical Field

[0001] The invention relates to a numerical simulation method for hydrothermal plume motion characteristics, in particular to a numerical simulation method for hydrothermal plume motion characteristics based on Fluent software. Background Art

[0002] Deep-sea hydrothermal circulation is an important bridge connecting the lithosphere, hydrosphere and biosphere, because hydrothermal cooling causes heat and chemicals to transfer from the lithosphere to the ocean. Seafloor hydrothermal activity areas are generally developed in ocean tectonic activity areas, and the most obvious manifestation of seafloor hydrothermal activity is: seawater infiltrates the seafloor through geothermal heating and water-rock reaction to become hydrothermal fluid, and then the high-temperature fluid is ejected from the seafloor hydrothermal vents and enters the seawater. Under the action of thermal buoyancy, it continues to rise in the ambient seawater, and quickly mixes with the surrounding cold seawater after meeting it. The mixed fluid can rise hundreds of meters until the neutral buoyancy layer, and begin to diffuse laterally. Its diffusion range can reach hundreds of kilometers in spatial scale, and finally form a hydrothermal plume.

[0003] Hydrothermal plumes can effectively affect a variety of processes such as mid-ocean ridge heat dissipation, regional water mixing, deep biosphere and ocean floor mineralization. Therefore, quantitative mechanism research on hydrothermal plumes will help to detect hydrothermal areas and hydrothermal vents faster and more accurately. Within a few hundred meters horizontally and vertically from the hydrothermal vents, convection and turbulent entrainment are the main characteristics of hydrodynamics. At present, the research on deep-sea hydrothermal plumes is more carried out through deep-sea in-situ measurements and laboratory simulations. In-situ measurements can only place sensors at specific locations on the seabed to obtain data at specific locations; laboratory simulations simulate underwater hydrothermal movement by artificial means. These two methods can only obtain limited detection data, and cannot quantitatively describe the movement state of hydrothermal at each point and at each moment. In addition, the cost of deep-sea detection or simulation of deep-sea environments is very high. Due to the limitations of observation capabilities and means, our understanding of the process of deep-sea hydrothermal plumes is relatively limited. Summary of the invention

[0004] Traditional methods such as in-situ measurement and laboratory simulation methods have many problems: low detection efficiency, less detection data obtained, high detection cost, inability to simulate the movement of the plume, unsuitable for quantitative analysis of the hydrothermal plume movement process, etc., which hinder the quantitative detection and research of submarine hydrothermal plumes. In order to solve the above problems, the present invention provides a numerical simulation method of the hydrothermal plume movement characteristics based on Fluent software, and verifies the effectiveness of the simulation method by comparing with field measured data.

[0005] The present invention provides a numerical simulation method for the motion characteristics of a hydrothermal plume based on Fluent software, comprising the following steps: S1. constructing a custom function:

[0006] (1) Obtaining actual detection data of seafloor hydrothermal plumes,

[0007] (2) Construct custom functions for seawater density, turbulent viscosity, specific heat capacity, and thermal conductivity that vary with seawater temperature;

[0008] (3) Construct a custom function for linear vertical temperature field;

[0009] S2. Establishment of kinetic model:

[0010] The continuity equation obtained by mass conservation is,

[0011] Based on the conservation of momentum, the Reynolds stress is linked to the average velocity gradient through the turbulent viscosity hypothesis, and the unsteady Reynolds time-averaged Navier-Stokes equation is obtained.

[0012] Based on the law of energy conservation, the temperature flux is linked to the average temperature gradient through the gradient diffusion hypothesis, resulting in the Reynolds average energy equation:

[0013] The k-ε turbulence model is used to describe the plume motion. The turbulent kinetic energy k and the turbulent dissipation rate ε are solved using the transport equations shown below,

[0014]

[0015]

[0016] For the incompressible fluid G b = 0, the turbulent viscosity coefficient of the plume motion is as follows

[0017]

[0018] S3. Grid division:

[0019] Draw the geometric model,

[0020] Set the maximum rise range of the plume,

[0021] Covering the axisymmetric slice with an unstructured triangular mesh,

[0022] The grid distribution feature is that the grid becomes sparse from bottom to top and from the middle to the sides.

[0023] The mesh quality is judged by the mesh skewness index to prevent the numerical simulation from diverging and ensure the accuracy of the analysis results.

[0024] S4. Numerical solution to determine the maximum rise height of the plume and the calculation formula of the neutral buoyancy layer height;

[0025] S5. Output simulation results representing the plume motion characteristics.

[0026] Preferably, step S4 comprises the following steps:

[0027] S41 sets boundary conditions:

[0028] Set the nozzle as the velocity inlet boundary condition, the bottom of the fluid domain as the no-slip boundary condition, the top of the fluid domain as the pressure outlet boundary condition, and the boundaries of other fluid domains as fixed walls.

[0029] Set the environment parameters,

[0030] Set the eruption velocity of the hydrothermal fluid and the flow velocity in other areas of the fluid domain except the vent.

[0031] Set the eruption temperature of the hydrothermal fluid, set the temperature field of the fluid domain to a linear vertical change from bottom to top, set the bottom seawater temperature and the top seawater temperature, and construct the temperature field function according to the linear temperature field conditions.

[0032] Set the distance between the nozzle and the horizon, and the distance between the nozzle and the seabed.

[0033] Set no backflow at the outlet, set the gauge pressure of the pressure outlet boundary condition to 0, and always maintain a constant static pressure so that the fluid can flow in and out of the boundary.

[0034] Set up seawater material,

[0035] The salinity during the plume movement is set to vary within a small range.

[0036] Set the relationship between seawater density, specific heat, thermal conductivity and turbulent viscosity and seawater temperature;

[0037] S42. Choice of solution method:

[0038] The plume dynamics model was selected by using Ansys-Fluent simulation analysis to obtain a numerical solution: the k-ε model in the turbulence model was selected, and the PISO algorithm based on the pressure-velocity coupling equation was selected as the solver;

[0039] S43. Boundary initialization and setting of iteration parameters:

[0040] The control equations are discretized into a set of algebraic equations using the finite volume method.

[0041] Set the total integration time of the simulation, select transient calculation, and set the time step and number of sub-step iterations;

[0042] S44. Determine whether the calculation has converged as a condition for terminating the Fluent calculation

[0043] S45. Determine the maximum rise height of the plume and the calculation formula for the height of the neutral buoyancy layer

[0044] By comparing the buoyancy frequency N and source buoyancy flux B under different working conditions, the coefficients k1 and k2 are obtained, and then the calculation formula for the maximum rise height of the plume and the height of the neutral buoyancy layer is obtained.

[0045]

[0046] Preferably, step S3 further comprises the following steps:

[0047] S31. Before drawing the geometric model, make an axisymmetric assumption: the movement of the hydrothermal plume in space can be regarded as a cylindrical fluid domain, and the plume rises along the center line of the bottom surface. In the motion view, the axisymmetric assumption of the spatial movement can be assumed to be a two-dimensional plane movement. The grid skewness index in step S3 is calculated using the following skewness coefficient formula:

[0048]

[0049] And the evaluation and value range of the skewness coefficient are as follows: excellent (0-0.25), very good (0.25-0.50), good (0.50-0.80), acceptable (0.80-0.95), poor (0.95-0.98), and unacceptable (0.98-1).

[0050] Preferably, the method for determining the top seawater temperature in step S41 is: setting different top seawater temperature values ​​according to each experimental control group, and constructing a temperature field function T=2.2+0.01H according to the linear temperature field condition. When setting the seawater material in step S41, the seawater material is set to pure water.

[0051] Preferably, the actual detection data of the seafloor hydrothermal plume obtained in step S1 includes: water depth, terrain flatness, maximum temperature of the outlet fluid of the vent, seawater temperature near the vent, buoyancy frequency of the background layer seawater, height of the neutral buoyancy layer plume, maximum rise height, and vertical velocity of the outlet fluid of the hydrothermal vent.

[0052] Preferably, the total integration time of the simulation in step S43 is 4t*, that is, the simulation of the entire plume eruption process can be completed within 4t* time, where t* is the buoyancy time scale; transient calculation is selected, the time step is set to 0.05s, and the number of sub-step iterations is 20, so that the motion characteristics of the plume at 0.05*n can be obtained, where n is an arbitrary natural number.

[0053] Preferably, in step S44, the momentum, turbulent kinetic energy, turbulent dissipation and energy equations are all spatially discretized using the high-precision third-order MUSCL format in the calculation; the PRESTO! scheme is used for discretization, and the discrete continuity balance is used for the staggered control quantity around the face to calculate the staggered pressure; the gradient algorithm adopts the node-based Greengauss method, the pressure-velocity coupling scheme adopts the PISO scheme, and the time discretization uses the second-order implicit format.

[0054] Preferably, step S45 further includes the following steps: setting different numerical simulation conditions: (1) only changing the ejection velocity of the nozzle; (2) only changing the background seawater temperature at the top of the fluid domain; (3) only changing the fluid temperature of the nozzle, and comprehensively analyzing the influence of the nozzle fluid velocity, nozzle fluid temperature and background layer seawater temperature on the movement of the hydrothermal plume. The actual nozzle source buoyancy flux B is calculated as follows:

[0055]

[0056] Where T1′ is the seawater temperature at the seafloor, T2 is the temperature of the hydrothermal plume at the outlet of the fluid domain, v1 is the velocity of the plume at the vent, and d is the diameter of the vent.

[0057] Principle of the present invention: The Fluent software used in the present invention is a general software for numerically solving fluid flow problems based on the principles of computational fluid dynamics. It uses an advanced k-ε turbulence closed model to describe turbulence and the entrainment and mixing processes caused by it, and adopts grid and simulation methods to comprehensively consider the influence of various factors on the motion characteristics of hydrothermal plumes. Calling the dynamic mesh model that is closest to the real physical state in Fluent software can simulate the flow process of the fluid at the boundary of the fluid domain and in the region; according to the collected data of the hydrothermal vents, through the regression fitting data processing method, construct the custom functions of seawater density, turbulent viscosity, specific heat capacity and thermal conductivity that change with the seawater temperature respectively; according to the temperature of the seabed and the top of the fluid domain, construct a custom function of the linear vertically changing temperature field; calling these programs in the corresponding settings of Fluent software, and setting the velocity temperature inlet boundary conditions and the pressure outlet boundary conditions, you can realize the numerical simulation of the deep-sea hydrothermal plume movement process, and obtain cloud maps such as velocity vector, temperature, turbulent kinetic energy and turbulent dissipation rate; through multiple groups of control experiments, analyze the parameter sensitivity, explore the limitations of the existing theoretical model, and then intuitively analyze the motion characteristics of the hydrothermal plume, and finally optimize the numerical simulation method of the motion characteristics of the hydrothermal plume.

[0058] Beneficial effects of the present invention: 1. The present invention can simulate the distribution and diffusion process of seafloor hydrothermal plumes, thereby providing a physical driving force for the development of numerical simulations of hydrothermal plume chemistry and biological processes; at the same time, it can also shorten the cycle of marine biological research and reduce costs. Compared with the two conventional detection and simulation methods of deep-sea in-situ measurement and laboratory simulation, the method provided by the present invention can obtain motion data of any part and any movement time point during the plume eruption process through numerical simulation, and can obtain results that are relatively consistent with the actual detection data; in addition, it has the advantage of low operating cost and is very suitable for quantitative analysis of hydrothermal plume movement processes.

[0059] 2. The present invention uses the dynamic grid model in Fluent software and the user-defined function of Fluent software to customize the functions of seawater density, turbulent viscosity, specific heat capacity and thermal conductivity that change with seawater temperature, the function of linear vertical temperature field, and set the velocity temperature inlet boundary conditions and pressure outlet boundary conditions. The numerical simulation of the hydrothermal plume movement process is achieved, the diffusion morphology of the hydrothermal plume is reproduced, and the simulation process is closer to the actual situation. The present invention is suitable for the simulation of the movement process of deep-sea hydrothermal plumes under different vent physical conditions. At present, the research on hydrothermal plume models is not perfect enough, especially the numerical simulation of hydrothermal plumes using Fluent software is even less. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 Front view of the axisymmetric fluid domain of the hydrothermal plume.

[0061] Figure 2 This is a local view of the nozzle of the axisymmetric fluid domain of the hydrothermal plume.

[0062] Figure 3 This is the simulation result diagram of the hydrothermal plume velocity field and temperature field.

[0063] Figure 4 This is a diagram showing the simulation results of the turbulent viscosity of the hydrothermal plume.

[0064] Figure 5 This is a diagram showing the simulation results of the turbulent kinetic energy of the hydrothermal plume.

[0065] Figure 6 This is a diagram showing the simulation results of the turbulent dissipation rate of the hydrothermal plume. DETAILED DESCRIPTION

[0066] The present invention is described in detail below with reference to specific embodiments, but this is by no means a limitation of the present invention.

[0067] Example

[0068] A numerical simulation method for the motion characteristics of a hydrothermal plume based on Fluent software specifically comprises the following steps:

[0069] S1. Build custom functions

[0070] (1) Obtaining actual detection data of seafloor hydrothermal plumes

[0071] Obtain actual detection data of seafloor hydrothermal plumes, including water depth, terrain flatness, maximum temperature of the outlet fluid of the vent, seawater temperature near the vent, buoyancy frequency of the background seawater, height of the neutral buoyancy layer plume, maximum rising height, and vertical velocity of the outlet fluid of the hydrothermal vent.

[0072] Take the ABE hydrothermal area of ​​the Lau Basin as an example. The Lau Basin is a semi-enclosed submarine basin located in the tropical South Pacific, west of Tonga Island. It is developed between the Coville-Lau Ridge and the Tonga-Kermadec Ridge. It is the first young submarine basin confirmed to be a back-arc basin, and there are many active low-temperature and high-temperature hydrothermal vents in the basin. In the eastern part of the Lau Basin, hydrothermal vents are mostly distributed along the expansion center of the eastern Lau Basin. Among them, there are 6 hydrothermal fields that have been discovered, and the ABE hydrothermal area is one of them. The ABE hydrothermal area has high-temperature hydrothermal vents with an average temperature of more than 200℃. The A1 hydrothermal vent is a typical high-temperature vent in the ABE hydrothermal area. The water depth is 2140m and the terrain is relatively flat. It is convenient to measure the data related to the rising plume. Therefore, this case chooses the A1 hydrothermal vent in the northern part of the ABE hydrothermal area to make the best estimate of the steady-state plume.

[0073] Jiang et al. (2014) measured the A1 hydrothermal vent, which consists of at least four closely adjacent holes, each with a diameter of 0.07 m. The total area of ​​the four holes is 0.0154 m2, which is equivalent to an effective hole with a diameter of 0.14 m. Therefore, the A1 vent in the ABE hydrothermal area is set as a single hole with a diameter of 0.14 m. The sea water temperature near the vent is 2.20 °C.

[0074] In 2011, Mottl et al. measured the local environment of the ABE hydrothermal area using CTD (conductivity-temperature-depth meter) and found that the maximum temperature of the fluid at the vent was 309°C and the seawater temperature near the vent was 2.2°C. They used the measured data to estimate the buoyancy frequency of the background seawater to be 0.0005 / s, the height of the neutral buoyancy layer of the plume to be 150m, the maximum rise height to be 200m, and iteratively estimated that the vertical velocity of the fluid at the hydrothermal vent was 0.20m / s.

[0075] (2) Based on the data collected from the hydrothermal vents, a custom function was constructed to show how seawater density, turbulent viscosity, specific heat capacity, and thermal conductivity change with seawater temperature through regression fitting data processing methods;

[0076] (3) Based on the temperatures of the seabed and the top of the fluid domain, a custom function of the linear vertically varying temperature field is constructed.

[0077] S2. Establishment of kinetic model

[0078] (1) Assumptions before modeling;

[0079] The dynamic characteristics of hydrothermal plumes need to consider the effects of many factors, such as the geometric characteristics of hydrothermal vents, irregular seafloor topography, eruption patterns that change over time, and seawater layer structure. Therefore, before the model is established, assumptions are made about the seawater depth, geological environment, whether the seawater is stratified, whether the seawater is compressible, the shape of the hydrothermal vents, and the bottom flow of the seawater in the hydrothermal area.

[0080] (2) Motion analysis of hydrothermal plumes;

[0081] The movement and diffusion process of hydrothermal plumes is mainly driven by buoyancy and is mostly in a turbulent flow state. The buoyancy of hydrothermal plumes is a function of:

[0082]

[0083] Where F is the buoyancy of the fluid, ρ is the density of the hydrothermal plume, ρ′ is the density of the background seawater, ΔT1 is the temperature difference between the upper and lower boundaries of the fluid domain, and α is the thermal expansion coefficient.

[0084] The density of seawater in the background layer changes with temperature. Different temperature fields will lead to different buoyancy frequencies, which are calculated as follows:

[0085]

[0086] Where N is the buoyancy frequency and H is the height of the fluid domain from the seabed.

[0087] There are many factors that affect the diffusion morphology of hydrothermal plumes on the seafloor, the most important of which are the height of the hydrothermal plume rise, the background ocean currents, and the seafloor topography. The maximum rise of the hydrothermal plume, that is, the maximum height that the hydrothermal plume can rise from the vent, is calculated as follows:

[0088] Z max =k1(B·N -3 ) 1 / 4 (3)

[0089] Where Z max is the maximum rise height of the plume, B is the source buoyancy flux, and k1 is the coefficient, which can be simulated.

[0090] (3) Establishment of plume motion control equations

[0091] According to the movement of deep-sea hydrothermal plumes in the ocean, their movement can be described by the Reynolds time-averaged fluid dynamics equations, specifically the continuity equation (4), the motion equation (5) and the energy equation (6).

[0092] The continuity equation obtained from the conservation of mass:

[0093]

[0094] Where t is time, x i is the spatial rectangular coordinate system, ρ is the fluid density, u i is the average speed.

[0095] In terms of momentum conservation, the Reynolds stress is linked to the average velocity gradient through the turbulent viscosity hypothesis (Boussinesq hypothesis), and the unsteady Reynolds time-averaged Navier-Stokes equations are obtained.

[0096]

[0097] In the above formula, ρ is pressure, μ is molecular viscosity, and u is i i is the pulsation speed, g i is the body force, τ ij is the strain rate tensor,

[0098]

[0099] In terms of energy conservation, the temperature flux is linked to the average temperature gradient through the gradient diffusion hypothesis, resulting in the Reynolds average energy equation.

[0100]

[0101] E is the total energy per unit mass of fluid, k is the effective thermal conductivity, T is the thermodynamic temperature, μ e is the effective viscosity, δ ij is the Kronecker symbol.

[0102] Considering the effect of buoyancy on the generation and dissipation of turbulent kinetic energy, the two-equation realizable k-ε turbulence model, which can better predict the circular jet diffusion flow, is selected to describe the plume motion. The turbulent kinetic energy k and the turbulent dissipation rate ε are solved using the transport equations shown in equations (7) and (8), respectively.

[0103]

[0104]

[0105] For the incompressible fluid G b =0.

[0106] The turbulent viscosity coefficient of the plume motion is given by:

[0107]

[0108] S3. Grid division

[0109] (1) Axisymmetric assumption: The motion of the hydrothermal plume in space can be regarded as a cylindrical fluid domain, and the plume rises along the center line of the bottom surface. In the motion view, the spatial motion is assumed to be axially symmetric as a two-dimensional plane motion, which can greatly reduce the amount of calculation.

[0110] (2) Draw the geometric model and mesh: Select the DesignModeler function of the Workbench module under Ansys to draw the geometric model. Set the maximum rise domain of the plume, and use the Mesh function of the Workbench module under Ansys to draw the mesh, and use the unstructured triangular mesh to cover the axisymmetric section. The mesh distribution characteristics are: from bottom to top, from the middle to the sides, the mesh gradually becomes sparse.

[0111] In this case, according to the general movement characteristics of hydrothermal plumes, the maximum rise range of the plume is set to 400m, the vent is approximately a horizontal line with a diameter of 0.14m, and the vent is 2m away from the seabed ( Figure 1 ). Based on the geometric model, the mesh is drawn through the Mesh function of the Workbench module under Ansys, and the axisymmetric section is covered with an unstructured triangular mesh. The chemical reaction of the plume in the nozzle area is the most significant, so the densest mesh is set near the nozzle. A denser mesh will facilitate more accurate calculations. The mesh in the area below 200m is appropriately dense; that is, overall, from bottom to top, from the middle to the sides, the mesh gradually becomes sparse. Due to the axisymmetric model, the nozzle mesh is divided into 20 equal parts, that is, the nozzle mesh is the smallest, with a size of 0.007m. It is gradually enlarged from the nozzle mesh to the fluid domain boundary at a constant rate of 1.02. The top edge of the fluid domain is evenly discretized into 50 segments with a mesh size of 4m. After mesh statistics, the entire area is divided into 56,334 meshes.

[0112] (3) Use the skewness coefficient to judge the quality of the mesh. Good mesh quality can enhance convergence, improve calculation accuracy, and reduce calculation time: To check the quality of the mesh, a high-quality mesh is needed to ensure the accuracy of the analysis results. Fluent software provides 8 parameters for evaluating mesh quality. In this method, the skewness coefficient is used to measure the mesh quality. As a means of checking the quality of the mesh, this coefficient is used to determine whether the mesh shape is close to the ideal state. Its definition is as follows:

[0113]

[0114] When the skew coefficient is 0, it means that the closer it is to the ideal state, the better the mesh quality; on the contrary, when it is closer to 1, the worse the mesh quality. The evaluation and value range of the skew coefficient are as follows: excellent (0-0.25), very good (0.25-0.50), good (0.50-0.80), acceptable (0.80-0.95), poor (0.95-0.98), unacceptable (0.98-1).

[0115] The maximum skewness coefficient of the mesh obtained by the method of the present invention is 0.67531, and the average skewness coefficient is 0.081331, which satisfies the skewness coefficient of the non-uniform triangular mesh less than 0.8. Its evaluation level is "good", so the mesh quality is good, the simulation operation will not diverge, and the accuracy of the analysis results can be ensured.

[0116] S4. Set boundary conditions

[0117] The nozzle is set as the velocity inlet boundary condition; the bottom of the fluid domain is set as the no-slip boundary condition, that is, the seabed is set as the no-slip boundary condition; the top of the fluid domain is set as the pressure outlet boundary condition; the boundaries of other fluid domains are set as fixed walls.

[0118] Set environmental parameters: set the eruption velocity of the hydrothermal fluid and the flow velocity in other places in the flow field, set the eruption temperature of the hydrothermal fluid, set the linear vertical change of the temperature field of the fluid domain from bottom to top, set the bottom seawater temperature, the top seawater temperature, construct the temperature field function according to the linear temperature field conditions, set the distance between the nozzle and the horizon, the distance between the nozzle and the seabed, set no backflow at the outlet, set the gauge pressure of the pressure outlet boundary condition to 0, always maintain a constant static pressure so that the fluid can flow in and out of the boundary, set the salinity during the plume movement to vary within a small range, and set the relationship between seawater density, specific heat, thermal conductivity and turbulent viscosity and seawater temperature.

[0119] In this case, the specific environment parameters are set as follows:

[0120] (1) The eruption velocity of the hydrothermal fluid is set to 0.2 m / s, and the flow velocity in other areas of the fluid domain except the nozzle is set to zero.

[0121] (2) The eruption temperature of the hydrothermal fluid is set to 309°C; the temperature field of the fluid domain presents a linear vertical change from bottom to top, where the bottom seawater temperature is set to 2.20°C, and different top seawater temperature values ​​are set according to each experimental control group. Based on the linear temperature field conditions, the temperature field function T = 2.2 + 0.01H is constructed.

[0122] (3) The nozzle is set 2000m away from the horizon and 2m away from the seabed.

[0123] (4) It is approximately assumed that there is no backflow at the outlet, and the gauge pressure of the pressure outlet boundary condition is set to 0. The static pressure is always maintained constant so that the fluid can flow in and out of the boundary.

[0124] (5) Choose pure water as the seawater material: because at the current temperature, pressure and salinity, the turbulent viscosity and thermal conductivity of pure water have little effect on the simulation results compared to seawater.

[0125] (6) The salinity during plume movement is assumed to vary within a small range.

[0126] (7) Setting seawater characteristics: The relationship between seawater density, specific heat, thermal conductivity, turbulent viscosity and seawater temperature is obtained through quintic linear regression fitting.

[0127] S4. Numerical solution to determine the maximum rise height of the plume and the calculation formula of the neutral buoyancy layer height;

[0128] 1. Choice of solution method

[0129] The plume dynamics model was selected by Ansys-Fluent simulation analysis to obtain a numerical solution: the k-ε model in the turbulence model was selected, the main parameter settings involved in the model are shown in Table 1, and the solver selected was the PISO algorithm based on the pressure-velocity coupling equation.

[0130] Table 1. Values ​​of turbulence equation parameters

[0131]

[0132] 2. Boundary initialization and setting iteration parameters

[0133] The control equations are discretized into a set of algebraic equations through the discretization method of the finite volume method. The total integration time of the simulation is set, transient calculation is selected, and the time step and sub-step iteration number are set.

[0134] In this case, according to the motion characteristics of the plume, the total integration time of the simulation is set to 4t* (t* is the buoyancy time scale), that is, within 4t*, the simulation of the entire plume eruption process can be completed. Select transient calculation, set the time step to 0.05s, and the number of sub-step iterations to 20, and the motion characteristics of the plume at 0.05*n (n is an arbitrary natural number) can be obtained.

[0135] 3. Determine whether the calculation has converged as a condition for terminating the Fluent calculation

[0136] The termination of Fluent calculation is mostly determined by whether the calculation has reached convergence. However, whether convergence has been achieved cannot be simply determined by whether the parameters in the residual graph tend to be flat, and the order of magnitude of the residual is not always the smaller the better. It is also necessary to analyze whether the changes in parameters are consistent with objective facts, such as monitoring the physical quantities such as velocity and temperature in the flow field that do not change with time, that is, relevant conservation is achieved. At this time, it should be noted that when convergence is not good, the relaxation factor should be adjusted. When the relaxation factor is smaller, the convergence conditions can be improved, making the calculation more stable, but the convergence time becomes longer. In the model calculation process of this case, the size of the relaxation factor is shown in Table 2 below.

[0137] Table 2 Relaxation factor values

[0138]

[0139] In order to reduce numerical dissipation and ensure the rationality of numerical simulation results, the momentum, turbulent kinetic energy, turbulent dissipation and energy equations are all spatially discretized using the high-precision third-order MUSCL format in the calculation; since the momentum equation has a pressure gradient term and the pressure gradient is relatively large, the PRESTO! scheme is used for discretization, and the discrete continuity balance is used for the "staggered" control quantity around the face to calculate the "staggered" pressure; the gradient algorithm uses the node-based Greengauss method, the pressure-velocity coupling scheme uses the PISO scheme, and the time discretization uses the second-order implicit format.

[0140] 4. Determine the maximum rise height of the plume and the calculation formula for the height of the neutral buoyancy layer

[0141] Different numerical simulation conditions were set: (1) only changing the vent's eruption velocity; (2) only changing the background seawater temperature at the top of the fluid domain; (3) only changing the vent's fluid temperature. The effects of the vent's fluid velocity, vent's fluid temperature, and background seawater temperature on the motion of the hydrothermal plume were comprehensively analyzed.

[0142] In the simulation, B is not the near buoyancy flux, but the source buoyancy flux of the actual nozzle, which is calculated as follows:

[0143]

[0144] Where T1′ is the seawater temperature at the seafloor, T2 is the temperature of the hydrothermal plume at the outlet of the fluid domain, v1 is the velocity of the plume at the vent, and d is the diameter of the vent.

[0145] By comparing the buoyancy frequency N and source buoyancy flux B under different working conditions, the coefficients k1 and k2 are obtained, and then the calculation formulas for the maximum rise height of the plume and the height of the neutral buoyancy layer are derived.

[0146]

[0147] S5. Output simulation results representing the plume motion characteristics.

[0148] At the beginning of the operation, we determine whether the turbulence at the inlet and outlet is consistent to determine whether the entire movement satisfies the mass conservation. After the calculation is completed, our simulation results include velocity vector field, turbulence field, temperature field, density field, and mixing ratio field. In order to observe the changes in the vertical inlet and outlet velocity, temperature, and turbulent viscosity of the plume, the Fluent post-processing toolkit is used to draw the results of the hydrothermal plume movement into corresponding velocity vector diagrams, temperature linear change diagrams, and turbulent viscosity cloud diagrams, such as Figures 3 to 6 shown.

[0149] Results verification analysis. The maximum rise height and neutral buoyancy layer height of the hydrothermal plume are calculated, as shown in Table 3. It can be seen that: first, the plume diffuses laterally in the neutral buoyancy layer, and the height of the neutral buoyancy layer is about 70% of the maximum rise height; second, under the same working conditions, the numerical simulation of the plume model is compared with the measured data, and the deviation rate of the maximum rise height and the neutral buoyancy layer height does not exceed 5%, which proves the correctness and reliability of this model.

[0150] Table 3 Numerical simulation experiments and their results

[0151]

Claims

1. A numerical simulation method for the motion characteristics of hydrothermal plumes based on Fluent software, characterized in that: The following steps are involved: S1. Build a custom function: (1) Obtain actual detection data of seafloor hydrothermal plumes; (2) Construct custom functions for seawater density, turbulent viscosity, specific heat capacity, and thermal conductivity that vary with seawater temperature; (3) Construct a custom function for linear vertical temperature field; S2. Establishment of kinetic model: The continuity equation is obtained through the conservation of mass, Based on the conservation of momentum, the Reynolds stress is linked to the average velocity gradient through the turbulent viscosity hypothesis, and the unsteady Reynolds time-averaged Navier-Stokes equation is obtained. Based on the law of energy conservation, the temperature flux is linked to the average temperature gradient through the gradient diffusion hypothesis, resulting in the Reynolds average energy equation: The k-ε turbulence model is used to describe the plume motion. The turbulent kinetic energy k and the turbulent dissipation rate ε are solved using the transport equations shown below, For the incompressible fluid G b =0, the turbulent viscosity coefficient of the plume motion is as follows: S3. Grid division: Draw the geometric model, Set the maximum rise range of the plume, Covering the axisymmetric slice with an unstructured triangular mesh, The grid distribution feature is that the grid becomes sparse from bottom to top and from the middle to the sides. The quality of the grid is judged by the grid skewness index; S4. Numerical solution to determine the maximum rise height of the plume and the calculation formula of the neutral buoyancy layer height; S5. Output simulation results representing the plume motion characteristics.

2. The method for numerically simulating the motion characteristics of a hydrothermal plume based on Fluent software according to claim 1, characterized in that: The S4 comprises the following steps: S41 sets boundary conditions: Set the nozzle as the velocity inlet boundary condition, the bottom of the fluid domain as the no-slip boundary condition, the top of the fluid domain as the pressure outlet boundary condition, and the boundaries of other fluid domains as fixed walls. Set the environment parameters, Set the eruption velocity of the hydrothermal fluid and the flow velocity in other areas of the fluid domain except the vent. Set the eruption temperature of the hydrothermal fluid, set the temperature field of the fluid domain to a linear vertical change from bottom to top, set the bottom seawater temperature and the top seawater temperature, and construct the temperature field function according to the linear temperature field conditions. Set the distance between the nozzle and the horizon, and the distance between the nozzle and the seabed. Set no backflow at the outlet, set the gauge pressure of the pressure outlet boundary condition to 0, and always maintain a constant static pressure so that the fluid can flow in and out of the boundary. Set up seawater material, The salinity during the plume movement is set to vary within a small range. Set the relationship between seawater density, specific heat, thermal conductivity and turbulent viscosity and seawater temperature; S42. Choice of solution method: The plume dynamics model was selected by using Ansys-Fluent simulation analysis to obtain a numerical solution: the k-ε model in the turbulence model was selected, and the PISO algorithm based on the pressure-velocity coupling equation was selected as the solver; S43. Boundary initialization and setting of iteration parameters: The control equations are discretized into a set of algebraic equations using the finite volume method. Set the total integration time of the simulation, select transient calculation, and set the time step and number of sub-step iterations; S44. Determine whether the calculation has converged, as a condition for terminating the Fluent calculation; S45. Determine the maximum rise height of the plume and the calculation formula for the height of the neutral buoyancy layer By comparing the buoyancy frequency N and source buoyancy flux B under different working conditions, the coefficients k1 and k2 are obtained, and then the calculation formula for the maximum rise height of the plume and the height of the neutral buoyancy layer is obtained.

3. A numerical simulation method for hydrothermal plume motion characteristics based on Fluent software as claimed in claim 1 or 2, characterized in that: In step S3, before drawing the geometric model, an axisymmetric assumption is made: the movement of the hydrothermal plume in space can be regarded as a cylindrical fluid domain, and the plume rises along the center line of the bottom surface. In the motion view, the axisymmetric assumption of the spatial motion can be assumed as a two-dimensional plane motion.

4. A numerical simulation method for hydrothermal plume motion characteristics based on Fluent software as claimed in claim 1 or 2, characterized in that: The grid skewness index in step S3 is calculated using the following skewness coefficient formula: And the evaluation and value range of the skewness coefficient are as follows: excellent 0-0.25, very good 0.25-0.50, good 0.50-0.80, acceptable 0.80-0.95, poor 0.95-0.98, and unacceptable 0.98-1.

5. The method for numerically simulating the motion characteristics of a hydrothermal plume based on Fluent software according to claim 2, characterized in that: The method for determining the top seawater temperature in step S41 is: setting different top seawater temperature values ​​according to each experimental control group, and constructing a temperature field function T=2.2+0.01H according to the linear temperature field condition.

6. The numerical simulation method of the motion characteristics of a hydrothermal plume based on Fluent software as claimed in claim 2, characterized in that: In the step S41, the seawater material is set to be pure water.

7. A numerical simulation method for hydrothermal plume motion characteristics based on Fluent software as claimed in claim 1 or 2, characterized in that: The actual detection data of the seafloor hydrothermal plume obtained in S1 include: water depth, terrain flatness, maximum temperature of the outlet fluid of the vent, seawater temperature near the vent, buoyancy frequency of the background layer seawater, height of the neutral buoyancy layer plume, maximum rising height, and vertical velocity of the outlet fluid of the hydrothermal vent.

8. A numerical simulation method for hydrothermal plume motion characteristics based on Fluent software as claimed in any one of claims 2, 5 and 6, characterized in that: The total integration time of the simulation in S43 is 4t*, that is, the simulation of the entire plume eruption process can be completed within 4t* time, where t* is the buoyancy time scale; transient calculation is selected, the time step is set to 0.05s, and the number of sub-step iterations is 20, and the motion characteristics of the plume at 0.05*n can be obtained, where n is an arbitrary natural number.

9. A numerical simulation method for hydrothermal plume motion characteristics based on Fluent software as claimed in claim 8, characterized in that: In the S44, the momentum, turbulent kinetic energy, turbulent dissipation, and energy equations are all spatially discretized using the high-precision third-order MUSCL format; the PRESTO! scheme is used for discretization, and the discrete continuity balance is used for the staggered control quantity around the face to calculate the staggered pressure; the gradient algorithm uses the node-based Greengauss method, the pressure-velocity coupling scheme uses the PISO scheme, and the time discretization uses the second-order implicit format.

10. A numerical simulation method for hydrothermal plume motion characteristics based on Fluent software according to any one of claims 2, 5 and 6, characterized in that: The S45 also includes setting different numerical simulation conditions: (1) only changing the ejection velocity of the nozzle; (2) only changing the background seawater temperature at the top of the fluid domain; (3) only changing the fluid temperature of the nozzle, and comprehensively analyzing the influence of the nozzle fluid velocity, nozzle fluid temperature and background layer seawater temperature on the movement of the hydrothermal plume. The actual source buoyancy flux B of the nozzle is calculated as follows: Where T1' is the seawater temperature at the seafloor, T2 is the temperature of the hydrothermal plume at the outlet of the fluid domain, v1 is the velocity of the plume at the vent, and d is the diameter of the vent.

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