CN114036870A - Hydrothermal plume motion characteristic numerical simulation method based on Fluent software - Google Patents
Hydrothermal plume motion characteristic numerical simulation method based on Fluent software Download PDFInfo
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Abstract
The invention relates to a numerical simulation method of hydrothermal plume movement characteristics based on Fluent software. The method specifically comprises the following steps: firstly, constructing a self-defined function; secondly, establishing a dynamic model; thirdly, dividing grids; solving numerical values, and determining a calculation formula of the maximum rising height of the plume and the height of the neutral buoyancy layer; and fifthly, outputting a solving result. The invention can simulate the change of each parameter of the hot liquid plume, which is helpful for understanding the material transportation and energy circulation of the ocean; meanwhile, compared with the traditional deep sea in-situ measurement, the method has the advantages of low cost and complete data. The result shows that under the same working condition, the maximum rising height of the simulation result compared with the actual measurement result is basically consistent with the height of the neutral buoyancy layer, and the error is less than 5%.
Description
Technical Field
The invention relates to a numerical simulation method of hydrothermal plume movement characteristics, in particular to a numerical simulation method of hydrothermal plume movement characteristics based on Fluent software.
Background
Deep sea hydrothermal circulation is an important bridge connecting the rock formation, water formation and biosphere, as hydrothermal cooling results in the transfer of heat and chemicals from the rock formation to the sea. The submarine hydrothermal solution activity area is generally developed in the ocean structure activity area, and the most obvious expression process of the submarine hydrothermal solution activity is as follows: the seawater permeates into the seabed through geothermal heating and water rock reaction to form hydrothermal fluid, then high-temperature fluid is sprayed out from a hydrothermal nozzle on the seabed and enters the seawater, the high-temperature fluid continuously rises in the environmental seawater under the action of thermal buoyancy, and is rapidly mixed after meeting with surrounding cold seawater, the mixed fluid can rise for hundreds of meters until reaching a neutral buoyancy layer and starts to laterally diffuse, the diffusion range can reach hundreds of kilometers in the spatial scale, and a hydrothermal plume is finally formed.
The hydrothermal plume can effectively influence the heat dissipation of the ridges in the ocean, the mixing of regional water bodies, deep biospheres, the mineralization of ocean bottoms and other processes. Therefore, quantitative mechanism research on the hydrothermal plume will help to detect the hydrothermal area and the hydrothermal vent position more quickly and accurately. Convection and turbulence entrainment are the main features of hydrodynamics in the range of hundreds of meters horizontally and vertically from the hydrothermal vents. At present, deep sea hydrothermal plume is researched more by deep sea in-situ measurement and laboratory simulation, and the in-situ measurement can only be carried out by arranging a sensor at a specific position on the seabed to acquire data of the specific position; the laboratory simulation is to simulate underwater hydrothermal fluid movement in a manual mode. The two modes can only obtain limited detection data, can not quantitatively describe the motion state of the hydrothermal fluid at each point and each moment, and have high cost for deep sea detection or deep sea environment simulation. Our knowledge of the process of deep-sea hydrothermal plume is relatively limited due to the limitations of observational capability means.
Disclosure of Invention
The traditional methods such as in-situ measurement and laboratory simulation methods have many problems: the method has the advantages of low detection efficiency, less acquired detection data and high detection cost, can not simulate the motion condition inside the plume, is not suitable for quantitative analysis of the motion process of the hydrothermal plume and the like, and hinders quantitative detection and research on the hydrothermal plume on the seabed. In order to solve the problems, the invention provides a numerical simulation method of hydrothermal plume movement characteristics based on Fluent software, and the validity of the simulation method is verified by comparing with field measured data.
The invention provides a numerical simulation method of hydrothermal plume movement characteristics based on Fluent software, which comprises the following steps: s1, constructing a custom function:
(1) obtaining the actual detection data of the submarine hydrothermal plume,
(2) constructing self-defined functions of seawater density, turbulent flow viscosity, specific heat capacity and heat conductivity which respectively change along with the seawater temperature;
(3) constructing a custom function of the linear vertical variation temperature field;
s2, establishing a dynamic model:
the continuity equation obtained by conservation of mass,
based on momentum conservation, the Reynolds stress is linked with the average velocity gradient through the assumption of turbulent viscosity to obtain a Navier-Stokes equation of the constant Reynolds time,
based on energy conservation, the temperature flux is connected with the average temperature gradient through the assumption of gradient diffusion to obtain a Reynolds average energy equation,
describing the plume motion by using a k-epsilon turbulence mode, solving turbulence kinetic energy k and turbulence dissipation rate epsilon by using transport equations shown in the following formula respectively,
wherein for incompressible fluid GbThe turbulent viscosity coefficient of the plume motion is as follows, 0 ═ 0
S3, grid division:
drawing a geometric model, and drawing a geometric model,
the maximum rising region of the plume is set,
covering the axisymmetric tangent plane with a non-structural triangular mesh,
the grid distribution is characterized in that the grids become sparse gradually from bottom to top and from the middle to two sides,
the grid quality is judged through the grid skewness index, the effect of preventing numerical simulation divergence is achieved, and the accuracy of an analysis result is ensured;
s4, numerical value solving is carried out, and a calculation formula of the maximum rising height of the plume and the height of the neutral buoyancy layer is determined;
and S5, outputting a simulation result representing the plume movement characteristics.
Preferably, step S4 includes the steps of:
s41 sets boundary conditions:
setting the nozzle as speed inlet boundary condition, the bottom of fluid domain as no-slip boundary condition, the top of fluid domain as pressure outlet boundary condition, the boundaries of other fluid domains as fixed wall surface,
the parameters of the environment are set up,
the burst speed of the hot liquid and the flow rate of other areas of the fluid area besides the nozzle are set,
setting the burst temperature of the hydrothermal fluid, setting the temperature field of the fluid domain to be linearly and vertically changed from bottom to top, setting the bottom seawater temperature and the top seawater temperature, constructing a temperature field function according to the conditions of the linear temperature field,
the distance between the nozzle and the ground level and the distance between the nozzle and the seabed are set,
setting the outlet to have no backflow, setting the gauge pressure of the pressure outlet boundary condition to 0, and always maintaining a constant static pressure, so that the fluid can flow into and out of the boundary,
the seawater material is arranged in the seawater tank,
the salinity during the plume movement is set to vary within a small range,
setting the relation between the seawater density, specific heat, heat conductivity coefficient and turbulent viscosity and the seawater temperature;
s42, selecting a solution:
selecting Ansys-Fluent simulation analysis by a plume dynamics model to obtain a numerical solution: selecting a k-epsilon model in a turbulence model, and selecting a PISO algorithm based on a pressure-velocity coupling equation by a solver;
s43, initializing a boundary and setting iteration parameters:
the control equation is dispersed by a dispersion method of a finite volume method to obtain an algebraic equation set,
setting total integration time of simulation, selecting transient calculation, and setting time step length and sub-step iteration number;
s44, judging whether the calculation is converged or not as a condition for terminating the Fluent calculation
S45, determining a calculation formula of maximum rising height of plume and height of neutral buoyancy layer
Obtaining a coefficient k by comparing buoyancy frequency N and source buoyancy flux B under different working conditions1And coefficient k2Further obtain the calculation formula of the maximum rising height of the plume and the height of the neutral buoyancy layer
Preferably, step S3 further includes the steps of:
s31, before drawing the geometric model, carrying out axial symmetry assumption: the motion of the thermal liquid plume in the space can be regarded as a fluid domain of a cylinder, the plume ascends along the center line of the bottom surface, and in the motion view, the spatial motion axis symmetry can be assumed as a two-dimensional plane motion. The grid skewness index in the step S3 is calculated by using the following skewness coefficient formula:
and the evaluation and value range of the deflection coefficient is as follows: excellent (0 to 0.25), very good (0.25 to 0.50), good (0.50 to 0.80), acceptable (0.80 to 0.95), poor (0.95 to 0.98), unacceptable (0.98 to 1).
Preferably, the method for determining the temperature of the top seawater in the step S41 is as follows: different values of the top seawater temperature are set according to the experimental control group, and a temperature field function T is constructed to be 2.2+0.01H according to the linear temperature field condition. When the seawater material is set in the step S41, the seawater material is set to pure water.
Preferably, the actual detection data of the submarine hydrothermal plume obtained in step S1 includes: including water depth, terrain flatness, highest outlet fluid temperature of the nozzle, seawater temperature near the nozzle, buoyancy frequency of the seawater in the background layer, plume height of the neutral buoyancy layer, maximum rise height, and vertical velocity of the outlet fluid of the hydrothermal nozzle.
Preferably, the total integration time of the simulation in step S43 is 4t, i.e. within 4t, the simulation of the whole process of plume eruption can be completed, where t is the time scale of buoyancy; transient calculation is selected, the time step is set to be 0.05s, the number of substep iterations is 20, and the motion characteristic of the plume at the time of 0.05 × n can be obtained, wherein n is any natural number.
Preferably, in step S44, high-precision third-order muscle format space dispersion is adopted for the momentum, turbulent kinetic energy, turbulent dissipation and energy equation in the calculation; using PRESTO! Solution discretization, balancing discrete continuity for the amount of control interleaving around the face to calculate interleaving pressure; the gradient algorithm adopts a Green Gaussian method based on nodes, a pressure velocity coupling scheme adopts a PISO scheme, and time dispersion adopts a second-order implicit format.
Preferably, step S45 further includes the following steps: different numerical simulation working conditions are set: (1) only the firing speed of the nozzle is changed; (2) only the background seawater temperature at the top of the fluid field is changed; (3) only the fluid temperature of the nozzle is changed, the influence conditions of the nozzle fluid speed, the nozzle fluid temperature and the background layer seawater temperature on the hydrothermal plume movement are comprehensively analyzed, the source buoyancy flux B of the actual nozzle is calculated according to the following formula:
in the formula, T1' is the temperature of the seawater at the seabed, T2Is the fluid domain outlet hydrothermal plume temperature, v1Is the velocity of the plume at the nozzle, and d is the nozzle diameter.
The principle of the invention is as follows: the Fluent software adopted by the invention is general software for solving the fluid flow problem based on the numerical value of the computational fluid dynamics principle, an advanced k-epsilon turbulence closed model is used for describing turbulence and a rolling and mixing process caused by the turbulence, and the influence of various factors on the motion characteristic of the hydrothermal plume is comprehensively considered by adopting a grid and a simulation method. Calling a dynamic grid model which is closest to a real physical state in Fluent software, and simulating the flowing process of fluid in the fluid domain boundary and the region; according to the collected data of the hydrothermal nozzle, a self-defined function of seawater density, turbulent flow viscosity, specific heat capacity and thermal conductivity which are respectively changed along with the seawater temperature is constructed by a regression fitting data processing method; constructing a self-defined function of a linear vertical change temperature field according to the temperatures of the seabed and the top of the fluid domain; calling the programs in the corresponding setting of Fluent software, and setting the speed-temperature inlet boundary condition and the pressure outlet boundary condition, so that the numerical simulation of the deep-sea hydrothermal plume motion process can be realized, and cloud charts such as speed vectors, temperature, turbulent kinetic energy, turbulent dissipation rate and the like are obtained; through a plurality of groups of comparison experiments, parameter sensitivity is analyzed, the limitation of the existing theoretical model is discussed, the movement characteristics of the hydrothermal plume are further visually analyzed, and finally, the optimization of the numerical simulation method of the movement characteristics of the hydrothermal plume is realized.
The invention has the beneficial effects that: 1. the invention can simulate the distribution and diffusion process of the hydrothermal plume at the sea bottom, thereby providing a physical driving force for the development of numerical simulation of the chemical and biological processes of the hydrothermal plume; meanwhile, the period of marine organism research can be shortened, and the cost is reduced. Compared with two conventional detection and simulation modes of deep sea in-situ measurement and laboratory simulation, the method provided by the invention can obtain the motion data of any position and any motion time point in the plume eruption process through numerical simulation, and can obtain a result which is more consistent with actual detection data; in addition, the method also has the advantage of low operation cost, and is very suitable for quantitative analysis of the movement process of the hot liquid plume.
2. By means of a dynamic grid model in Fluent software, and by utilizing the function of a Fluent software user-defined function, the numerical simulation of the movement process of the hydrothermal plume is realized by defining a function of the seawater density, the turbulent viscosity, the specific heat capacity and the heat conductivity which respectively change along with the seawater temperature, a function of a linear vertical change temperature field and setting a speed temperature inlet boundary condition and a pressure outlet boundary condition, the diffusion form of the hydrothermal plume is reproduced, and the simulation process is closer to the actual situation. The method is suitable for simulating the deep-sea hydrothermal fluid plume movement process under different nozzle physical conditions. The research on the hydrothermal plume model is not complete at present, and particularly, numerical simulation of the hydrothermal plume is less by using Fluent software.
Drawings
FIG. 1 is a front view of a hydrothermal plume axially symmetric fluid domain.
FIG. 2 is a partial view of a nozzle with a hot plume axis symmetric fluid field.
FIG. 3 is a graph of the simulation results of hydrothermal plume velocity field versus temperature field.
FIG. 4 is a graph of the results of a simulation of the turbulent viscosity of a hydrothermal plume.
FIG. 5 is a graph of simulation results of hydrothermal plume turbulence flow energy.
FIG. 6 is a graph of the results of a simulation of the thermal liquid plume turbulence dissipation ratio.
Detailed Description
The present invention is described in detail below with reference to specific examples, but the present invention is not limited thereto in any way.
Examples
A numerical simulation method for hydrothermal plume movement characteristics based on Fluent software specifically comprises the following steps:
s1, constructing a custom function
(1) Obtaining actual detection data of submarine hydrothermal plume
Acquiring actual detection data of the submarine hydrothermal plume, wherein the actual detection data comprises water depth, terrain leveling degree, the highest outlet fluid temperature of a nozzle, the seawater temperature near the nozzle, the buoyancy frequency of the seawater of a background layer, the height of the plume of a neutral buoyancy layer, the maximum rising height and the vertical velocity of the outlet fluid of the hydrothermal nozzle.
Taking the ABE hydrothermal area of the working basin as an example, the working basin is the west of the san jia island in the ground, a semi-closed submarine basin located in the tropical south pacific, which develops between the Coville-Lau ocean ridge and the Tonga-keradec ocean ridge, is the first young submarine basin to be identified as the posterior arc basin, and in which a number of active hydrothermal spouts at low and high temperatures are developed. In the east of Laowan, hydrothermal nozzles are distributed along the expansion center of the east Laowan, wherein 6 hydrothermal fields are found, one ABE hydrothermal area is one of the ABE hydrothermal areas, and the ABE hydrothermal area develops a high-temperature hydrothermal nozzle with the uniform temperature of more than 200 ℃. The A1 hydrothermal nozzle is a typical high-temperature nozzle in an ABE hydrothermal area, has water depth of 2140m, smooth terrain and convenient measurement work for relevant data of rising plumes, so that the optimal estimation of steady-state plumes is selected for the A1 hydrothermal nozzle in the northern part of the ABE hydrothermal area.
Jiang et al (2014) et al measured an A1 hydrothermal vent consisting of at least four closely adjacent holes, each hole having a diameter of 0.07m, the four holes having a total area of 0.0154m2, corresponding to an effective hole having a diameter of 0.14m, so that the A1 vent of the ABE hydrothermal zone was set to a single hole having a diameter of 0.14m and the seawater temperature near the vent was 2.20 ℃.
Mottl et al 2011 measured by CTD (conductivity-temperature-depth meter) in the local environment of the ABE hydrothermal area, the maximum temperature of the fluid at the nozzle was 309 ℃, the temperature of the seawater near the nozzle was 2.2 ℃, and the measured data was used to estimate the buoyancy frequency of the background layer 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 the iterative estimation of the vertical velocity of the fluid at the hydrothermal nozzle to be 0.20 m/s.
(2) According to the collected data of the hydrothermal nozzle, a self-defined function of seawater density, turbulent flow viscosity, specific heat capacity and thermal conductivity which are respectively changed along with the seawater temperature is constructed by a regression fitting data processing method;
(3) and constructing a custom function of the linear vertical variation temperature field according to the temperatures of the sea bottom and the top of the fluid domain.
S2, establishing a dynamic model
(1) Assumptions before modeling;
the dynamics of the hydrothermal plume need to take into account the effects of various factors, such as the geometric features of hydrothermal jets, irregular submarine topography, time-varying eruption pattern, and sea water layer structure. Therefore, before the model is established, the conditions of the seawater depth of the hydrothermal area, the geological environment, whether the seawater is layered or not, whether the seawater is compressible, the shape of the hydrothermal port, the bottom layer flow of the seawater and the like are assumed.
(2) Analysis of the movement of the hydrothermal plume;
the motion diffusion process of the hot liquid plume is mainly driven by buoyancy and is mostly in a turbulent flow regime. The buoyancy to which the hot liquid plume is subjected is functionally related to:
where F is the buoyancy to which the fluid is subjected, ρ is the hydrothermal plume density, ρ' is the background layer seawater density, Δ T1Is the temperature difference between the seawater at the upper and lower boundaries of the fluid domain, and alpha is the thermal expansion coefficient.
The density of the seawater in the background layer changes with the temperature. Different temperature fields result in different buoyancy frequencies, which are calculated as follows:
where N is the buoyancy frequency and H is the height of the fluid field from the sea floor.
There are many factors that affect the diffusion pattern of the hydrothermal plume on the seabed, most notably the hydrothermal plume rise height, background currents and the topography of the seabed. The maximum rising height of the hot liquid plume, i.e. the maximum height of the hot liquid plume from the nozzle orifice, is calculated as follows:
Zmax＝k1(B·N-3)1/4 (3)
wherein ZmaxThe maximum rise height of the plume, B the source buoyancy flux, and k1 the coefficients, can be modeled.
(3) Establishment of plume motion control equation
According to the motion situation of the deep-sea hydrothermal plume in the sea, the motion of the deep-sea hydrothermal plume can be described by fluid dynamic equations after Reynolds time averaging, and specifically, the fluid dynamic equations are a continuity equation (4), a motion equation (5) and an energy equation (6).
Continuity equation derived from conservation of mass:
wherein t is time, xiIs a space rectangular coordinate system, rho is the fluid density, uiIs the average velocity.
In terms of momentum conservation, the Reynolds stress is related to the average velocity gradient through a turbulent viscosity hypothesis (Boussinesq hypothesis), and a constant Reynolds time mean Navier-Stokes equation is obtained.
In the above formula, ρ is the pressure, μ is the molecular viscosity, u isii is the pulse velocity, giIs a volume force, τijIn order to be the strain rate tensor,
in terms of energy conservation, the Reynolds average energy equation is derived by linking the temperature flux to the average temperature gradient through the gradient diffusion assumption.
E isTotal energy per unit mass of fluid, k effective thermal conductivity, T thermodynamic temperature, μeTo effective viscosity, δijIs a kronecker symbol.
Considering the influence of buoyancy on the generation and dissipation of turbulent kinetic energy, a double-stroke realizable k-epsilon turbulent flow mode capable of well predicting circular jet diffusion flow is selected to describe the plume movement. The turbulent kinetic energy k and the turbulent dissipation ratio epsilon are solved by the transport equations shown in equations (7) and (8), respectively.
Wherein for incompressible fluid Gb＝0。
The turbulent viscosity coefficient of the plume movement is as follows.
S3, grid division
(1) The assumption of axial symmetry is: the movement of the hot liquid plume in space can be seen as a fluid domain of a cylinder, with the plume ascending along the centerline of the floor. In the motion view, the spatial motion axial symmetry is assumed to be two-dimensional plane motion, so that the calculation amount can be greatly reduced.
(2) Drawing a geometric model and a grid: and selecting a DesignModelr function of a Workbench module under Ansys to draw the geometric model. Setting the maximum rising area of the plume, drawing a grid through the Mesh function of a Workbench module under Ansys, and covering an axisymmetric tangent plane with an unstructured triangular grid. The grid distribution characteristics are as follows: from bottom to top, the grid becomes increasingly sparse from the middle to the sides.
In this case, according to the general motion characteristics of the hot liquid plume, the maximum rising area of the plume is set to 400m, the nozzle is approximately a transverse line with a diameter of 0.14m and a distance of 2m from the sea bottom (fig. 1). On the basis of a geometric model, a Mesh function of a Workbench module under Ansys is used for drawing a Mesh, and an axial symmetry tangent plane is covered by a non-structural triangular Mesh. The chemical reaction of the plume in the nozzle area is most remarkable, so that the nozzle is arranged to be the most dense grid nearby, the denser grid is favorable for more accurate calculation, and the grid in the area below 200m is appropriately dense; i.e. overall, from bottom to top, from the middle to both sides, the grid becomes increasingly sparse. Due to the axisymmetric model, the mesh of the nozzle is divided into 20 equal parts, namely the nozzle mesh is the smallest and has the size of 0.007m, the nozzle mesh is gradually enlarged to the boundary of the fluid domain from the nozzle mesh at a constant rate of 1.02, the top edge of the fluid domain is uniformly dispersed into 50 segments, the mesh size is 4m, and the whole area is divided by 56,334 meshes through mesh statistics.
(3) The grid quality is judged through the grid deflection coefficient (Skewness), and the good grid quality can enhance convergence, improve the calculation precision and reduce the calculation time: checking the grid quality, the accuracy of the analysis result needs to be ensured by a high-quality grid, and the Fluent software provides 8 parameters for evaluating the grid quality. The method adopts a skewing coefficient (Skewness) to measure the grid quality. As a check means of the grid quality, the coefficient is used to determine whether the grid shape is close to an ideal state, and the definition is as follows:
when the deflection coefficient is 0, the closer to an ideal state, the better the grid quality is; conversely, closer to 1 indicates a poorer mesh quality. The evaluation and value range of the deflection coefficient is as follows: excellent (0 to 0.25), very good (0.25 to 0.50), good (0.50 to 0.80), acceptable (0.80 to 0.95), poor (0.95 to 0.98), unacceptable (0.98 to 1).
The maximum value of the deflection coefficient of the grid obtained by the method is 0.67531, the average value is 0.081331, the requirement that the deflection coefficient of the non-uniform triangular grid is less than 0.8, and the evaluation grade is 'good', so the grid quality is good, the simulation operation is not diverged, and the accuracy of the analysis result can be ensured.
S4, setting boundary conditions
Setting a nozzle as a speed inlet boundary condition; setting the bottom of the fluid domain as a non-slip boundary condition, namely setting the seabed as the non-slip boundary condition; setting the top of the fluid domain as a pressure outlet boundary condition; the boundary of the other fluid domains is set as a fixed wall surface.
Setting environmental parameters: setting the eruption speed and flow velocity of hydrothermal fluid at other places of the flow field, setting the eruption temperature of the hydrothermal fluid, setting the linear vertical change of the temperature field of the fluid domain from bottom to top, setting the bottom seawater temperature and the top seawater temperature, constructing a temperature field function according to the conditions of the linear temperature field, setting the distance between a nozzle and the horizon, setting the distance between the nozzle and the seabed, setting no backflow at an outlet, setting the gauge pressure of the boundary condition of a pressure outlet to be 0, always keeping constant static pressure, enabling the fluid to flow into and out of the boundary, setting the salinity in the plume movement process to be changed in a small range, and setting the relation between the seawater density, specific heat, heat conductivity and turbulence viscosity and the seawater temperature.
In this case, the specific environmental parameters are set as follows:
(1) the burst velocity of the hydrothermal fluid is set to 0.2m/s, and the flow velocity of the other areas except the nozzle in the fluid area is set to zero.
(2) Setting the burst temperature of the hot liquid fluid to 309 ℃; and the temperature field of the fluid domain shows linear vertical change from the bottom to the top, wherein the bottom seawater temperature is set to be 2.20 ℃, different top seawater temperature values are set according to the control group of each experiment, and the temperature field function T is constructed to be 2.2+0.01H according to the linear temperature field condition.
(3) The distance between the nozzle and the ground level is 2000m, and the distance between the nozzle and the seabed is 2 m.
(4) Approximately no backflow at the outlet was assumed, and the gauge pressure setting pressure outlet boundary conditions were 0, maintaining a constant static pressure throughout, allowing fluid to flow into and out of the boundary.
(5) Selecting pure water as a seawater material: because the turbulence viscosity and the thermal conductivity of pure water have little influence on the simulation results compared to seawater at the present temperature, pressure and salinity.
(6) The salinity during the plume movement is set to vary within a small range.
(7) Setting the seawater characteristics: and obtaining the relation between the seawater density, the specific heat, the heat conductivity coefficient and the turbulent viscosity and the seawater temperature through quintic linear regression fitting.
S4, numerical value solving is carried out, and a calculation formula of the maximum rising height of the plume and the height of the neutral buoyancy layer is determined;
1. selection of solution
Selecting Ansys-Fluent simulation analysis by a plume dynamics model to obtain a numerical solution: a k-epsilon model in a turbulence model is selected, main parameters related in the model are set as shown in table 1, and a PISO algorithm based on a pressure-velocity coupling equation is selected to solve by a solver.
TABLE 1 turbulence equation parameter values
2. Boundary initialization and setting iteration parameters
The control equation is dispersed through a dispersion method of a finite volume method to obtain an algebraic equation set, the total integration time of simulation is set, transient calculation is selected, and the time step length and the number of sub-step iterations are set.
In this case, the total integration time of the simulation is set to be 4t (t is the buoyancy time scale) according to the motion characteristics of the plume, that is, the simulation of the whole process of plume eruption can be completed within 4 t. Transient calculation is selected, the time step is set to be 0.05s, the number of substep iterations is 20, and the movement characteristics of the plume at the time of 0.05 × n (n is any natural number) can be obtained.
3. Judging whether the calculation is converged or not as a condition for terminating the Fluent calculation
Judging whether Fluent calculation is terminated is mostly according to whether the calculation reaches convergence, but whether the calculation reaches the convergence cannot be simply seen whether parameters in a residual error graph tend to be smooth or not, the order of magnitude of the residual error is not smaller or better, and whether the change of the parameters accords with objective facts or not is analyzed, for example, the speed, the temperature and other physical quantities in a monitoring flow field do not change along with time, namely, relevant conservation is achieved. At this point, it is noted that when convergence is not good, the relaxation factor is adjusted. As the relaxation factor is smaller, the convergence condition can be improved more, so that the calculation is more stable, but the convergence time becomes longer. The magnitude of the relaxation factor in the model calculation process of this case is shown in table 2 below.
TABLE 2 relaxation factor values
In order to reduce the numerical dissipation and ensure the rationality of the numerical simulation result, high-precision three-order MUSCL format space dispersion is adopted for momentum, turbulent kinetic energy, turbulent dissipation and an energy equation in the calculation; since the momentum equation has a pressure gradient term and the pressure gradient is large, use of PRESTO! Solution discretization, balancing discrete continuity for "staggered" control quantities around the face to calculate "staggered" pressures; the gradient algorithm adopts a Green Gaussian method based on nodes, a pressure velocity coupling scheme adopts a PISO scheme, and time dispersion adopts a second-order implicit format.
4. Calculation formula for determining maximum rising height of plume and height of neutral buoyancy layer
Different numerical simulation working conditions are set: (1) only the firing speed of the nozzle is changed; (2) only the background seawater temperature at the top of the fluid field is changed; (3) only the fluid temperature of the nozzle is changed. Comprehensively analyzing the influence of the spout fluid speed, the spout fluid temperature and the background layer seawater temperature on the movement of the hydrothermal plume.
In the simulation, B is not near buoyancy flux, but source buoyancy flux of the actual nozzle, and the calculation formula is as follows:
in the formula, T1' is the temperature of the seawater at the seabed, T2Is the fluid domain outlet hydrothermal plume temperature, v1Is the velocity of the plume at the nozzle, and d is the nozzle diameter.
Obtaining a coefficient k by comparing buoyancy frequency N and source buoyancy flux B under different working conditions1And coefficient k2And further obtaining a calculation formula of the maximum rising height of the plume and the height of the neutral buoyancy layer.
And S5, outputting a simulation result representing the plume movement characteristics.
At the beginning of operation, whether the whole movement meets the mass conservation is judged by judging whether the turbulence quantity of the inlet is consistent with that of the outlet. After the calculation is finished, the simulation results comprise a flow velocity vector field, a turbulent flow field, a temperature field, a density field, a mixing ratio field and the like. In order to observe the vertical inlet and outlet velocity, temperature, turbulence viscosity and other changes of the plume, a Fluent post-treatment toolkit is adopted to draw the motion result of the thermal liquid plume into corresponding velocity vector diagrams, temperature linear change diagrams, turbulence viscosity and other cloud diagrams, as shown in figures 3-6.
And (5) verifying and analyzing the result. The maximum rise height and neutral buoyancy layer height of the hydrothermal plume were calculated as shown in table 3, and it can be seen that: firstly, the plume is laterally diffused in a neutral buoyancy layer, and the height of the neutral buoyancy layer is about 70% of the maximum rising height; secondly, under the same working condition, comparing the plume model numerical simulation with the measured data, wherein the deviation rate of the maximum rising height and the height of the neutral buoyancy layer does not exceed 5 percent, and the correctness and the reliability of the model are proved.
TABLE 3 numerical simulation test and results thereof
Claims (10)
1. A numerical simulation method for hydrothermal plume movement characteristics based on Fluent software is characterized by comprising the following steps:
s1, constructing a custom function:
(1) acquiring actual detection data of the submarine hydrothermal plume;
(2) constructing self-defined functions of seawater density, turbulent flow viscosity, specific heat capacity and heat conductivity which respectively change along with the seawater temperature;
(3) constructing a custom function of the linear vertical variation temperature field;
s2, establishing a dynamic model:
the continuity equation obtained by conservation of mass,
based on momentum conservation, the Reynolds stress is linked with the average velocity gradient through the assumption of turbulent viscosity to obtain a Navier-Stokes equation of the constant Reynolds time,
based on energy conservation, the temperature flux is connected with the average temperature gradient through the assumption of gradient diffusion to obtain a Reynolds average energy equation,
describing the plume motion by using a k-epsilon turbulence mode, solving turbulence kinetic energy k and turbulence dissipation rate epsilon by using transport equations shown in the following formula respectively,
wherein for incompressible fluid GbThe turbulent viscosity coefficient of plume movement is 0 as follows:
s3, grid division:
drawing a geometric model, and drawing a geometric model,
the maximum rising region of the plume is set,
covering the axisymmetric tangent plane with a non-structural triangular mesh,
the grid distribution is characterized in that the grids become sparse gradually from bottom to top and from the middle to two sides,
judging the grid quality through the grid skewness index;
s4, numerical value solving is carried out, and a calculation formula of the maximum rising height of the plume and the height of the neutral buoyancy layer is determined;
and S5, outputting a simulation result representing the plume movement characteristics.
2. The method for numerical simulation of hydrothermal plume movement characteristics based on Fluent software according to claim 1, wherein the S4 comprises the following steps:
s41 sets boundary conditions:
setting the nozzle as speed inlet boundary condition, the bottom of fluid domain as no-slip boundary condition, the top of fluid domain as pressure outlet boundary condition, the boundaries of other fluid domains as fixed wall surface,
the parameters of the environment are set up,
the burst speed of the hot liquid and the flow rate of other areas of the fluid area besides the nozzle are set,
setting the burst temperature of the hydrothermal fluid, setting the temperature field of the fluid domain to be linearly and vertically changed from bottom to top, setting the bottom seawater temperature and the top seawater temperature, constructing a temperature field function according to the conditions of the linear temperature field,
the distance between the nozzle and the ground level and the distance between the nozzle and the seabed are set,
setting the outlet to have no backflow, setting the gauge pressure of the pressure outlet boundary condition to 0, and always maintaining a constant static pressure, so that the fluid can flow into and out of the boundary,
the seawater material is arranged in the seawater tank,
the salinity during the plume movement is set to vary within a small range,
setting the relation between the seawater density, specific heat, heat conductivity coefficient and turbulent viscosity and the seawater temperature;
s42, selecting a solution:
selecting Ansys-Fluent simulation analysis by a plume dynamics model to obtain a numerical solution: selecting a k-epsilon model in a turbulence model, and selecting a PISO algorithm based on a pressure-velocity coupling equation by a solver;
s43, initializing a boundary and setting iteration parameters:
the control equation is dispersed by a dispersion method of a finite volume method to obtain an algebraic equation set,
setting total integration time of simulation, selecting transient calculation, and setting time step length and sub-step iteration number;
s44, judging whether the calculation is converged or not, and taking the convergence as a condition for terminating the Fluent calculation;
s45, determining a calculation formula of maximum rising height of plume and height of neutral buoyancy layer
Obtaining a coefficient k by comparing buoyancy frequency N and source buoyancy flux B under different working conditions1And coefficient k2Further obtain the calculation formula of the maximum rising height of the plume and the height of the neutral buoyancy layer
3. The method for numerical simulation of hydrothermal plume movement characteristics based on Fluent software according to claim 1 or 2, wherein in step S3, before drawing the geometric model, axial symmetry assumption is made: the motion of the thermal liquid plume in the space can be regarded as a fluid domain of a cylinder, the plume ascends along the center line of the bottom surface, and in the motion view, the spatial motion axis symmetry can be assumed as a two-dimensional plane motion.
4. The numerical simulation method for hydrothermal plume movement characteristics based on Fluent software according to claim 1 or 2, wherein the grid skewness index in the step S3 is calculated by using the following skewness coefficient formula:
and the evaluation and value range of the deflection coefficient is as follows: excellent (0 to 0.25), very good (0.25 to 0.50), good (0.50 to 0.80), acceptable (0.80 to 0.95), poor (0.95 to 0.98), unacceptable (0.98 to 1).
5. The numerical simulation method for hydrothermal plume movement characteristics based on Fluent software according to claim 2, wherein the determination method of the top seawater temperature in the step S41 is: different values of the top seawater temperature are set according to the experimental control group, and a temperature field function T is constructed to be 2.2+0.01H according to the linear temperature field condition.
6. The numerical simulation method for hydrothermal plume movement characteristics based on Fluent software according to claim 2, wherein the seawater material is pure water in the step S41.
7. The numerical simulation method for hydrothermal plume movement characteristics based on Fluent software according to claim 1 or 2, wherein the actual detection data of the submarine hydrothermal plume obtained in S1 includes: water depth, terrain leveling degree, highest outlet fluid temperature of the nozzle, seawater temperature near the nozzle, buoyancy frequency of seawater in a background layer, plume height of a neutral buoyancy layer, maximum rising height and vertical velocity of outlet fluid of the hydrothermal nozzle.
8. The method for numerical simulation of motion characteristics of hot liquid plumes based on Fluent software according to any one of claims 2, 5 and 6, wherein the total integration time of the simulation in S43 is 4t, i.e. the simulation of the whole process of plume eruption can be completed within 4t, wherein t is a buoyancy time scale; transient calculation is selected, the time step is set to be 0.05s, the number of substep iterations is 20, and the motion characteristic of the plume at the time of 0.05 × n can be obtained, wherein n is any natural number.
9. The method of claim 8, wherein in S44, high-precision third-order muscle scale spatial dispersion is adopted for momentum, turbulent kinetic energy, turbulent dissipation and energy equation in the calculation; using PRESTO! Solution discretization, balancing discrete continuity for the amount of control interleaving around the face to calculate interleaving pressure; the gradient algorithm adopts a Green Gaussian method based on nodes, a pressure velocity coupling scheme adopts a PISO scheme, and time dispersion adopts a second-order implicit format.
10. The method for numerically simulating hot liquid plume movement characteristics based on Fluent software according to any one of claims 2, 5 and 6, wherein the step S45 further comprises setting different numerically simulated conditions: (1) only the firing speed of the nozzle is changed; (2) only the background seawater temperature at the top of the fluid field is changed; (3) only the fluid temperature of the nozzle is changed, the influence conditions of the nozzle fluid speed, the nozzle fluid temperature and the background layer seawater temperature on the hydrothermal plume movement are comprehensively analyzed, the source buoyancy flux B of the actual nozzle is calculated according to the following formula:
in the formula, T1' is the temperature of the seawater at the seabed, T2Is the fluid domain outlet hydrothermal plume temperature, v1Is the velocity of the plume at the nozzle, and d is the nozzle diameter.
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