CN113688555A - Water body pollution diffusion simulation prediction method and device based on concentration analysis - Google Patents
Water body pollution diffusion simulation prediction method and device based on concentration analysis Download PDFInfo
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Abstract
A water body pollution diffusion simulation prediction method and a device based on concentration analysis comprise the following steps: carrying out grid division on the simulation area according to small grids, recording the pollutant concentration at the center of each grid by using a numerical value, forming a concentration matrix representing pollutant distribution by using the numerical values corresponding to all the grids, and calculating the pollutant concentration change of each grid; dividing the concentration change process of the pollutants into three independent sub-processes, namely a migration process, a dispersion process and an attenuation process, analyzing and calculating the concentration matrix change caused by each sub-process, then superposing the sub-processes to obtain a pollutant diffusion process, and updating the concentration matrix correspondingly; and continuously and iteratively calculating a concentration matrix according to the time step, and representing the pollutant concentration at the corresponding grid area by using the numerical value in the concentration matrix, thereby realizing the simulation prediction of the pollutant diffusion process. The invention can realize the high-efficiency diffusion simulation prediction of various pollutants in water bodies, particularly large-range water bodies (such as ocean).
Description
Technical Field
The invention relates to analysis and prediction of a pollutant diffusion process in a water body, in particular to a water body pollution diffusion simulation prediction method and a water body pollution diffusion simulation prediction device based on concentration analysis.
Background
With the rapid development of global economy, the influence of human activities on the surrounding environment is increasing, and the problems of environmental pollution and ecological destruction caused by the human activities are receiving more and more attention. In the marine field, a series of events caused by human factors, such as industrial wastewater discharge, offshore crude oil leakage and the like, make marine ecological environment face a serious challenge. In order to describe and predict the diffusion behavior of pollutants in water more accurately, various diffusion models have been developed so far at home and abroad, such as a LAKECO model for a lake ecosystem, a vortex resolution model for ocean diffusion analysis, and the like, and diffusion analysis software combining finite element technology, such as TIDAL, HydroGeoSphere, MIKE3, and the like, appears. However, these diffusion simulation methods and analysis software have respective drawbacks, such as not considering the attenuation of radioactive elements, setting complex simulation parameters, requiring multiple environmental data as input, and the like, and particularly in the large-scale diffusion scene such as the ocean, it is difficult to sufficiently acquire the required input data, such as the wind field, temperature, and the like, which change with time, and there are problems that the simulation time is too long and is unacceptable.
It is to be noted that the information disclosed in the above background section is only for understanding the background of the present application and thus may include information that does not constitute prior art known to a person of ordinary skill in the art.
Disclosure of Invention
The invention mainly aims to overcome the defects of the background technology and provide a water body pollution diffusion simulation and prediction method and device based on concentration analysis.
In order to achieve the purpose, the invention adopts the following technical scheme:
a water body pollution diffusion simulation prediction method based on concentration analysis comprises the following steps: carrying out grid division on the simulation area according to small grids, recording the pollutant concentration at the center of each grid by using a numerical value, forming a concentration matrix representing pollutant distribution by using the numerical values corresponding to all the grids, and calculating the pollutant concentration change of each grid; dividing the concentration change process of the pollutants into three independent sub-processes, namely a migration process, a dispersion process and an attenuation process, analyzing and calculating the concentration matrix change caused by each sub-process, then superposing the sub-processes to obtain a pollutant diffusion process, and updating the concentration matrix correspondingly; and continuously and iteratively calculating a concentration matrix according to the time step, and representing the pollutant concentration at the corresponding grid area by using the numerical value in the concentration matrix, thereby realizing the simulation prediction of the pollutant diffusion process.
Further:
the dispersion process is analytically calculated by: for any two adjacent squares, the difference in contaminant concentration at the known center point is
After a simulation step, the concentration of contaminants in the low concentration squares will increase
While the concentration of contaminants in the high concentration squares will be reduced
When coefficient of dispersion
Giving the length of the edge of the small square along a certain direction when the length is kept constant
And simulated time step
After that time, the user can use the device,
is a constant value
Is marked as
，
Is the amount of concentration change.
The migration process is analytically calculated by: the flow velocity of the flow field at the central point of the small grid is v, and the components along two orthogonal directions are respectively
And
step of elapsed time
Then, the fluid infinitesimal at the central point of the small square will be along
Direction and
respectively go forward in direction
And
is reached to a new position, the concentration at the new position after the migration is equal to the concentration at the center of the cell before the migration, wherein, takeThe moving distance is the side length of the small square
Integral multiple of (d), fluid infinitesimal edges at the central point of the small grid
Direction and
the number of squares of the direction of advance is respectively recorded as
And
；
wherein each calculation
Only for each decentralized process, 1 migration process is calculated, i.e. the time steps of the decentralized process and the migration process are respectively
And
，
is a positive integer, and the dispersion process is
Can be diffused in time
Distance of small squares, contamination in
Moving within time
The distance of the small squares meets the following conditions:
the attenuation process is analytically calculated by: when calculating the decay process, the concentration of all cells is multiplied by each time
，
And obtaining a new concentration matrix after the decay process for the decay constant.
The meshing and the time step are determined by:
selecting a proper rectangular or cuboid area containing a pollution source and a water body to be analyzed as one of the boundaries of pollutant diffusion and used for subsequent grid division; selecting the side length of the square grid according to the required calculation precision and the size of the simulation area
Then, the simulation area is uniformly divided into side lengths of
A square or cube of (a); then, analyzing the flow field of the water body to be analyzed to obtain the maximum flow velocity of the water body
The simulation time step of the dispersion process satisfies the following condition
Selecting an appropriate time step based on the condition
And is calculated according to the following formula
Value of
The time step of the migration process is
Wherein
Satisfies the following conditions
According to
This requirement determines the time step factor of the migration process
。
For the two-dimensional diffusion problem, it is checked whether the k value is less than
(ii) a For the three-dimensional diffusion problem, it is checked whether the k value is less than
(ii) a If not, reselecting a smaller time step
Until this requirement is met;
initializing a concentration matrix of a contamination diffusion simulation area by:
setting all elements in the concentration matrix to be 0, setting corresponding elements in the concentration matrix to be any negative numbers for the boundary part, marking the boundary special square grids by using the negative numbers, and then setting the concentration values of the square grids according to the concentration of each pollution source at the initial moment so as to finish the initialization of the concentration matrix.
Performing iterative computation on the concentration matrix, including:
from the present moment
Initially, the following steps are performed cyclically:
for each pollution source, judging whether pollutants are discharged at the current moment or not according to a predetermined pollutant discharge schedule and discharge amount, and if so, adding a corresponding pollutant concentration value to a square where the pollution source is located;
calculating the position of each element in the density matrix according to the current density matrix
The variable quantity in the concentration matrix is formed; wherein the variation of each element is calculated as follows: noting the value of the target element as
N non-negative elements adjacent thereto, if
Or
The variation of the target element is 0; otherwise, the sum of the n adjacent elements is recorded as
Then the variation of the target element is
(ii) a Obtaining a concentration variation matrixThen, adding the original concentration matrix to a concentration change matrix to obtain a new concentration matrix after the dispersion process occurs; this step repeats
Secondly;
the concentration matrix obtained from the previous step, and from time t to time t
Calculating the concentration of the center of each polluted square grid after the migration process occurs in the flow field in the time period to obtain a new concentration matrix; the specific calculation process is as follows: for any target square, from
Starting from the moment, reversely calculating the position of the central infinitesimal at the time t, wherein the concentration value of the square at the position at the time t is the concentration value of the target square at the time t
A concentration value at a time; wherein the pushing process is reversed
For a time interval, the backward shift is
Adding the sub-displacements to obtain; if the central micro element reaches the boundary square grid in the process, assuming that the central micro element does not move after reaching the vicinity of the boundary, only keeping the sub-displacement before reaching the boundary square grid;
multiplying each element in the density matrix by a coefficient
Obtaining a new concentration matrix after the attenuation process;
increase the current time
That is to say
And circularly executing the steps until t reaches the simulation end time.
Further comprising: and carrying out visual display in a graphic and animation mode according to the simulation result data.
A water body pollution diffusion simulation prediction device based on concentration analysis comprises: a processor and a computer readable storage medium storing a computer program which, when executed by the processor, performs the water body pollution diffusion simulation prediction method.
The invention has the following beneficial effects:
the invention provides a concentration analysis-based water body pollution diffusion simulation and prediction method, which can realize high-efficiency diffusion simulation and prediction of various pollutants (including radioactive elements) in a water body, particularly a large-range water body (such as ocean), so that the problems of analysis and prediction of the diffusion process and concentration distribution of the pollutants are solved.
Drawings
Fig. 1 is a schematic diagram of an embodiment of the present invention for dividing the process of concentration change of contaminants into three separate sub-processes, namely, a migration process, a dispersion process, and an attenuation process.
FIG. 2 is a schematic diagram of the derivation process of the computational principle of the decentralized process according to the present invention.
FIG. 3 is a calculation diagram of a single-step decentralized process according to an embodiment of the present invention.
FIG. 4 is a diagram illustrating a migration process calculation principle derivation process according to the present invention.
FIG. 5 is a calculation diagram of a single-step migration process according to an embodiment of the present invention.
Fig. 6 is a schematic view of a modular structure according to an embodiment of the present invention.
FIG. 7 is a dynamic display of the contaminant diffusion process and concentration profile according to one embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be described in detail below. It should be emphasized that the following description is merely exemplary in nature and is not intended to limit the scope of the invention or its application.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element. In addition, the connection may be for either a fixed or coupled or communicating function.
It is to be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in an orientation or positional relationship indicated in the drawings for convenience in describing the embodiments of the present invention and to simplify the description, and are not intended to indicate or imply that the referenced device or element must have a particular orientation, be constructed in a particular orientation, and be in any way limiting of the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of the present invention, "a plurality" means two or more unless specifically limited otherwise.
The embodiment of the invention provides a water body pollution diffusion simulation and prediction method based on concentration analysis, which comprises the steps of carrying out grid division on a simulation area according to small grids, recording the pollutant concentration at the center of each grid by using a numerical value, forming a concentration matrix representing pollutant distribution by using the numerical values corresponding to all the grids, and calculating the pollutant concentration change of each grid; dividing the concentration change process of the pollutants into three independent sub-processes, namely a migration process, a dispersion process and an attenuation process, analyzing and calculating the concentration matrix change caused by each sub-process, then superposing the sub-processes to obtain a pollutant diffusion process, and updating the concentration matrix correspondingly; and continuously and iteratively calculating a concentration matrix according to the time step, and representing the pollutant concentration at the corresponding grid area by using the numerical value in the concentration matrix, thereby realizing the simulation prediction of the pollutant diffusion process.
The embodiment of the invention also provides a simulation prediction device based on the water body pollution diffusion simulation prediction method.
The method and the device can realize the high-efficiency diffusion simulation prediction of various pollutants (including radioactive elements) in the water body, particularly in a large-range water body (such as ocean), thereby solving the problems of the diffusion process and the concentration distribution analysis and prediction of the pollutants.
Specific embodiments of the present invention are further described below.
In the water body, the diffusion process of the pollutants can be represented by the concentration of the pollutants in different areas at various time points, so that the simulation of the diffusion process of the pollutants is realized by analyzing the change of the concentration of the pollutants in the water body within a certain time period. Specifically, the present invention divides the process of concentration change of the contaminant into three separate sub-processes, which are a migration process, a dispersion process, and an attenuation process, respectively, as shown in fig. 1. The migration process refers to a directional movement process of the pollutants along with the ocean current, and the process only changes the positions of the pollutants and does not change the concentration of the pollutants; the dispersion process refers to a process of transporting pollutants from a high-concentration area to a low-concentration area caused by concentration gradient, and is mainly influenced by the effects of molecular diffusion, turbulent diffusion under local turbulence, dispersion caused by uneven cross-sectional flow velocity and the like; the decay process refers to a process in which the pollutant is converted into other substances due to the decomposition, decay and the like of the pollutant, so that the concentration of the pollutant is reduced. The entire diffusion process is obtained by analyzing each sub-process individually and finally stacking the sub-processes. The calculation principles of these three sub-processes are explained below.
Dispersion process
The key characteristic of the dispersion process is that the concentration change of the pollutants is in direct proportion to the concentration gradient, the ratio of the concentration change to the concentration gradient is related to the molecular diffusion effect, the turbulent diffusion effect, the dispersion effect and the like, is called as a dispersion coefficient, and is expressed in the form of Fick's law as follows
Wherein D is a dispersion coefficient of the polymer,
for concentration gradient, J is the diffusion flux, meaning the total amount of contaminant per unit area per unit time.
Taking the two-dimensional dispersion problem (uniform distribution of contaminants along the height) as an example, a two-dimensional plane is divided into uniform small squares along which
Length of side in direction of
Edge of
Length of side in direction of
In general, the grid can be divided into small square grids
. Remember two edges
The concentration of the pollutants at the centers of the small squares which are adjacent in the direction is respectively
And
the difference being
As shown in fig. 2. Assuming that the concentration gradient between the central points of the two squares is constant, then
In a short time
In this case, the concentration value of the two squares is not changed greatly, and the concentration gradient is kept unchanged, so that the total amount of the pollutants passing through the contact surface of the two squares is
Wherein S is the area of the contact surface of the two squares, and if the height of the contact surface is h, then
. Before and after the pollutants pass through the contact surface of the small grids, the concentration variation of the two grids is
Namely, it is
As can be seen from the above formula, the dispersion coefficient is
Giving the length of the edge of the small square along a certain direction when the length is kept constant
And simulated time step
After that time, the user can use the device,
will be a constant value, noted
The k value represents the simulated velocity of the dispersion process, the significance of which can be understood by the following process: for any two adjacent squares, the difference in contaminant concentration at the known center point is
After a simulation step, the concentration of contaminants in the low concentration squares will increase
While the concentration of contaminants in the high concentration squares will be reduced
. The larger the k value, the fewer simulation steps are required to achieve a state of uniform concentration, but the more pronounced the concentration gradient changes during a single-step simulation (assuming the same previously), the less accurate the result. For square grid division, because
The k values in both directions will also be the same, and for simplification purposes, squares are defaulted to be squares in subsequent analysis processes. Furthermore, a single cell typically has 4 adjacent cells, which are satisfied by the convergence of the result
(ii) a For the three-dimensional dispersion problem, this critical value is
. It is also known from the meaning of the k value that the dispersion process is dependent only on the relative value of the concentration and not on the absolute value of the concentration. The calculation of the dispersion process is illustrated in fig. 3 by a simple example: the concentration of the central small square grid is 1 (relative value), the concentration of the peripheral small square grids is 0, and the central small square grid and the peripheral small square grids are taken
After a simulation step length, the concentration of the adjacent cells will be
The concentration of the central cell becomes
。
Migration process
During the migration process, only the directional movement of the pollutants with the ocean currents is considered, which is basically assumed to be: at the same time and same location, the contaminants have the same migration direction and migration velocity as the ocean current flow field. Also taking the two-dimensional migration problem as an example, assuming that the flow velocity of the flow field at the central point of the small grid is v, the components along two orthogonal directions are respectively
And
. Then, a short time passes
Then, the fluid infinitesimal at the central point of the small square will be along
Direction and
respectively go forward in direction
And
to a new position. At this time, it can be considered that the concentration at the new position after the transition is equal to the concentration at the center of the small square before the transition. Only recording the pollutant concentration at the central point of each small square, and taking the moving distance as the side length of the small square for keeping the grid division of the sea area unchanged
Integral multiples of (a). Note the book
(rounding up), the fluid infinitesimal edge at the central point of the small square grid
Direction and
the number of squares in the direction of advance can be recorded as
And
. Rounding of the data, however, can result in distortion of the data, e.g.,
and
are all equal to 1, but the expressions 0.5 and 1.4 differ greatly. In order to reduce the error caused by rounding operation, the speed size and speed direction information should be kept as much as possible
And
is a greater value, or
Much greater than 1.
Notably, at a single time step
In other words, the contaminants are dispersed into the adjacent cells, i.e., the dispersion process diffuses the contaminants by a distance of 1 cell, while the migration process moves the contaminants by about 1 cell
Distance of the small squares. If it is not
Above 1, the contaminants will not diffuse back into the water flow direction, resulting in a "vacuum zone" simulating contamination, as in FIG. 4 "
"check. This is in contrast to the requirements of the previous analysis
Are in contradiction. At this time, this problem can be solved by taking different time steps: per calculation
Only for each decentralized process, 1 migration process is calculated, i.e. the time steps of the decentralized process and the migration process are respectively
And
，
is a positive integer. In this way, the dispersion process is
Can be diffused in time
Distance of small squares, contamination in
Move about in time
The distance of the small squares can be only required to satisfy the following conditions.
Typically, a representative ocean current velocity (e.g., the maximum ocean current velocity) may be used
) Instead of in the above formula
And (6) performing calculation.
Another potential problem is that due to the deformability of the fluid, it may occur that the centers of a plurality of cells move inside the same cell after the migration process. As shown in fig. 5(a), after the migration, the central infinitesimal elements of both the panels a and c move into the panel d, while the central infinitesimal element without any element moves into the panel b. This will result in the case of a cell d with multiple density inputs and a cell b without density inputs when calculating the migration process. For this purpose, a reverse derivation method is adopted to calculate the migration process: for the center of each small square to be solved, calculating the fluid infinitesimal position
The position of the front panel, the pollutant concentration of the position is the pollutant concentration at the center of the small square after the migration occurs. As shown in fig. 5(B), for the small squares B and d to be solved, the uniquely determined points are corresponding to the centers of the small squares, and the method can ensure that each small square has unique concentration input data, thereby better meeting the analysis and calculation requirements of the migration process.
Attenuation process
For decay processes, such as the decay of a radioactive element, the time dependence of its concentration can be expressed as
Wherein c is the concentration of the contaminant,
is the decay constant. Thus, it can be deduced that any time passes
The concentration of the contaminant species will become the original
And (4) doubling. Decay constant and half-life
In a relationship of
For a single pollutant emission, the concentration of all cells is multiplied by the concentration of all cells each time, since the decay process is calculated
Whereas the calculation of the dispersion process is only related to the relative value of the concentration, the calculation of the migration process is also only related to the water flowThe data are related, so that instead of considering the decay process in each time segment, only the difference t between the start time and the end time of the diffusion process is known and the result of the calculation is multiplied by
And (4) finishing.
The specific process of the embodiment of the method is as follows:
(1) determining basic information of pollution diffusion process
The basic information of the process of pollution diffusion includes: the number of pollution sources, the positions, the discharge modes and the time schedules (one-time discharge or multiple discharge) of the pollution sources and the amount of discharged pollutants; boundaries of pollution diffusion, such as seacoasts, seabed, dams and other water bodies which are connected with the water body to be analyzed but can be ignored; thirdly, the dispersion coefficient D of the pollutants in the water body to be analyzed is used for calculating the subsequent dispersion process; fourthly, the flow field distribution of the water body to be analyzed in the simulation time period, namely the water flow speed of each point in the given time; attenuation constant of pollutant in water body to be analyzed
。
(2) Determining meshing and time step
Firstly, a proper rectangular or cuboid area containing a pollution source and a water body to be analyzed is selected to be used as one of the boundaries of pollutant diffusion and used for subsequent grid division. Selecting the side length of the square grid according to the required calculation precision and the size of the simulation area
Then, the simulation area is uniformly divided into side lengths of
Square or cube. Then, analyzing the flow field of the water body to be analyzed to obtain the maximum flow velocity of the water body
That isThe simulation time step of the process of dispersing satisfies the following conditions
Selecting an appropriate time step based on the condition
And calculating the k value according to the following formula
For the two-dimensional diffusion problem, it is checked whether the k value is less than
(ii) a For the three-dimensional diffusion problem, it is checked whether the k value is less than
. If not, reselecting a smaller time step
Until this requirement is met.
The time step of the migration process is
Wherein
Satisfies the following conditions
Can be generally approximated according to
This requirement determines the time of the migration processCoefficient of inter step
。
(3) Initializing a concentration matrix of a contamination diffusion simulation zone
For each square in the simulated area, the contaminant concentration at its center is recorded using a number that forms a concentration matrix representing the contaminant distribution. All elements in the density matrix are first set to 0 and then the corresponding elements in the density matrix are set to any negative number for the boundary portion (e.g., land). Since the concentration value of the contaminant cannot be negative, the border special squares can be marked with a negative number. Then, the concentration value of the square (at least 1 square, or a plurality of squares) is set according to the concentration of each pollution source at the initial time, so that the initialization of the concentration matrix is completed.
(4) Iterative computation of a concentration matrix
Current time of day
And circularly executing the following steps until t reaches the simulation end time.
And for each pollution source, judging whether the pollutants need to be discharged at the current moment or not according to the pollutant discharge schedule and the discharge amount, and if so, adding a corresponding pollutant concentration value to the square where the pollution source is located.
Calculating the position of each element in the density matrix according to the current density matrix
The variation quantity in the concentration matrix. Wherein the variation of each element is calculated as follows: noting the value of the target element as
N non-negative elements adjacent thereto (up-down, left-right, front-back), if
Or
The variation of the target element is 0; otherwise, the sum of the n adjacent elements is recorded as
Then the variation of the target element is
. And after the concentration change matrix is obtained, adding the original concentration matrix to the concentration change matrix to obtain a new concentration matrix after the dispersion process occurs. This step repeats
Next, the process is carried out.
The concentration matrix obtained from the previous step, and from time t to time t
And calculating the concentration of the center of each polluted square grid after the migration process occurs in the flow field in the time period to obtain a new concentration matrix. The specific calculation process is as follows: for any target square, from
Starting from the moment, reversely calculating the position of the central infinitesimal at the time t, wherein the concentration value of the square at the position at the time t is the concentration value of the target square at the time t
The concentration value at the time. Wherein the pushing process is reversed
For time intervals, due to each passage
The central element will reach the new position and the water velocity at the positionDifferent, so that the actual backward displacement is
And adding the sub-displacements. If the central element reaches the boundary square grid in the process, the central element is supposed not to move after reaching the vicinity of the boundary, and only the sub-displacement before reaching the boundary square grid is reserved.
Multiplying each element in the density matrix by a coefficient
A new concentration matrix after the attenuation process is obtained.
Increase the current time
That is to say
。
(5) Obtaining simulation results
For the condition that only the pollutant concentration distribution at the ending moment is needed, a final concentration matrix is reserved; and when the whole pollutant diffusion process is needed, the obtained concentration matrix is stored in each step of the circulation process of the process (4).
Based on the diffusion simulation prediction method, another embodiment provides a two-dimensional diffusion simulation device applicable to global oceans.
The simulation device can be divided into the following 4 modules: the device comprises a boundary management module, a flow field management module, a diffusion simulation module and a result display module. The relationship between the modules is shown in fig. 6, and the functions are as follows:
(1) boundary management module
For providing boundary information in the sea area, mainly the boundary between sea and land. The specific functions of the module are as follows: for each input longitude and latitude, a Boolean value can be output to indicate whether the position represented by the longitude and latitude is outside the simulated sea area, so as to determine the boundary of pollution diffusion.
(2) Flow field management module
For providing flow field information at the sea surface. The specific functions are as follows: outputting the ocean current speed at the corresponding sea surface at the corresponding moment for each input time and longitude and latitude; and outputting the peak flow velocity of the ocean current in the corresponding interval for the input time period and the latitude and longitude range.
(3) Diffusion simulation module
The core content of the iteration of the diffusion process is the management of a concentration matrix. The specific functions are as follows: reading boundary information from a boundary management module, setting pollution source information and initializing a concentration matrix; in each time step, sequentially calculating concentration matrix changes caused by pollution source emission, a dispersion process, a migration process and an attenuation process, and iterating the processes; and storing the calculated result in a grid data file.
(4) Result display module
And displaying the simulation result. The specific functions are as follows: and reading simulation result data from the grid data file, and performing visual display in a graphic and animation mode.
Examples of the invention
The device is realized through two programming languages of C # and python, wherein a program written by C # is mainly responsible for generation and iteration of a concentration matrix, and a simulation result is stored in a grid data file; and the program written by python is mainly responsible for the visual display of the simulation result.
(1) Boundary data
The boundary data is open source ETOPO1 terrain data (https:// www.ngdc.noaa.gov/mgg/global /), contains global elevation grid data divided by longitude and latitude, and has the data precision of 1/60 degrees. The boundary management module reads terrain data from the Etopo1 terrain data, and takes the part (land) with the elevation greater than or equal to 0 as a default boundary and the part (sea) with the elevation less than 0 as a simulated water body area.
(2) Ocean current data
Ocean current data is open source OSCAR data, comprises sea surface ocean current data between 80 degrees S and 80 degrees N since 1980, and has the data accuracy of 1/3 degrees and 5 days. And the flow field management module reads flow field data, namely ocean surface ocean current velocity of a specified position at a specified time from the OSCAR data, and provides the flow field data to the diffusion simulation module for calculation in the migration process.
(3) Netcdf-based pollutant concentration data storage
The Network Common Data Form (NetCDF) is a mesh Data format suitable for environment Data, and generally takes ". nc" as a file suffix. The device writes the concentration matrix into the NetCDF file in sequence according to the simulated time nodes in the diffusion simulation module, thereby realizing the persistent storage and management of the simulation data.
(4) Matplotlib-based result visualization
Matplotlib is an open source graphics library in python, and can draw and store graphics and animations in various formats. The device realizes dynamic display of the pollutant diffusion process and concentration distribution through functions such as an isoline color map in Matplotlib, and the like, as shown in FIG. 7.
The background of the present invention may contain background information related to the problem or environment of the present invention and does not necessarily describe the prior art. Accordingly, the inclusion in the background section is not an admission of prior art by the applicant.
The foregoing is a more detailed description of the invention in connection with specific/preferred embodiments and is not intended to limit the practice of the invention to those descriptions. It will be apparent to those skilled in the art that various substitutions and modifications can be made to the described embodiments without departing from the spirit of the invention, and these substitutions and modifications should be considered to fall within the scope of the invention. In the description herein, references to the description of the term "one embodiment," "some embodiments," "preferred embodiments," "an example," "a specific example," or "some examples" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction. Although embodiments of the present invention and their advantages have been described in detail, it should be understood that various changes, substitutions and alterations can be made herein without departing from the scope of the claims.
Claims (10)
1. A water body pollution diffusion simulation prediction method based on concentration analysis is characterized by comprising the following steps: carrying out grid division on the simulation area according to small grids, recording the pollutant concentration at the center of each grid by using a numerical value, forming a concentration matrix representing pollutant distribution by using the numerical values corresponding to all the grids, and calculating the pollutant concentration change of each grid; dividing the concentration change process of the pollutants into three independent sub-processes, namely a migration process, a dispersion process and an attenuation process, analyzing and calculating the concentration matrix change caused by each sub-process, then superposing the sub-processes to obtain a pollutant diffusion process, and updating the concentration matrix correspondingly; and continuously and iteratively calculating a concentration matrix according to the time step, and representing the pollutant concentration at the corresponding grid area by using the numerical value in the concentration matrix, thereby realizing the simulation prediction of the pollutant diffusion process.
2. The water body pollution diffusion simulation prediction method of claim 1, wherein the dispersion process is analytically calculated by: for any two adjacent squares, the difference in contaminant concentration at the known center point is
After a simulation step, the concentration of contaminants in the low concentration squares will increase
While the concentration of contaminants in the high concentration squares will be reduced
When coefficient of dispersion
Giving the length of the edge of the small square along a certain direction when the length is kept constant
And simulated time step
After that time, the user can use the device,
is a constant value
Is marked as
，
Is the amount of concentration change.
3. The water body pollution diffusion simulation prediction method of claim 2, wherein the migration process is analytically calculated by: the flow velocity of the flow field at the central point of the small grid is
The components in two orthogonal directions are respectively
And
step of elapsed time
Then, the fluid infinitesimal at the central point of the small square will be along
Direction and
respectively go forward in direction
And
the distance of the small square grid reaches a new position, the concentration of the new position after the migration is equal to the concentration of the center of the small square grid before the migration, wherein the moving distance is taken as the side length of the small square grid
Integral multiple of (d), fluid infinitesimal edges at the central point of the small grid
Direction and
the number of squares of the direction of advance is respectively recorded as
And
；
wherein each calculation
Only for each decentralized process, 1 migration process is calculated, i.e. the time steps of the decentralized process and the migration process are respectively
And
，
is a positive integer, and the dispersion process is
Can be diffused in time
Distance of small squares, contamination in
Moving within time
The distance of the small squares meets the following conditions:
4. the water body pollution diffusion simulation prediction method of claim 3, wherein the attenuation process is analytically calculated by: when calculating the decay process, the concentration of all cells is multiplied by each time
，
And obtaining a new concentration matrix after the decay process for the decay constant.
5. The water body pollution diffusion simulation and prediction method of any one of claims 1 to 4, wherein the grid division and the time step are determined by:
selecting a proper rectangular or cuboid area containing a pollution source and a water body to be analyzed as one of the boundaries of pollutant diffusion and used for subsequent grid division; selecting the side length of the square grid according to the required calculation precision and the size of the simulation area
Then, the simulation area is uniformly divided into side lengths of
A square or cube of (a); then, analyzing the flow field of the water body to be analyzed to obtain the maximum flow velocity of the water body
The simulation time step of the dispersion process satisfies the following condition
Selecting an appropriate time step based on the condition
And is calculated according to the following formula
Value of
The time step of the migration process is
Wherein
Satisfies the following conditions
According to
This requirement determines the time step factor of the migration process
。
6. The water body pollution diffusion simulation prediction method of claim 5, wherein for the two-dimensional diffusion problem, whether the k value is less than or equal to
(ii) a For the three-dimensional diffusion problem, it is checked whether the k value is less than
(ii) a If not, reselecting a smaller time step
Until this requirement is met.
7. The water body pollution diffusion simulation prediction method according to any one of claims 1 to 4, wherein the concentration matrix of the pollution diffusion simulation area is initialized by:
setting all elements in the concentration matrix to be 0, setting corresponding elements in the concentration matrix to be any negative numbers for the boundary part, marking the boundary special square grids by using the negative numbers, and then setting the concentration values of the square grids according to the concentration of each pollution source at the initial moment so as to finish the initialization of the concentration matrix.
8. The water body pollution diffusion simulation and prediction method of any one of claims 3 to 4, wherein the iterative calculation of the concentration matrix comprises:
from the present moment
Initially, the following steps are performed cyclically:
for each pollution source, judging whether pollutants are discharged at the current moment or not according to a predetermined pollutant discharge schedule and discharge amount, and if so, adding a corresponding pollutant concentration value to a square where the pollution source is located;
calculating the position of each element in the density matrix according to the current density matrix
The variable quantity in the concentration matrix is formed; wherein the variation of each element is calculated as follows: noting the value of the target element as
N non-negative elements adjacent thereto, if
Or
The variation of the target element is 0; otherwise, the sum of the n adjacent elements is recorded as
Then the variation of the target element is
(ii) a After the concentration change matrix is obtained, adding the original concentration matrix to the concentration change matrix to obtain a new concentration matrix after the dispersion process occurs; this step repeats
Secondly;
the concentration matrix obtained from the previous step, and from time t to time t
Calculating the concentration of the center of each polluted square grid after the migration process occurs in the flow field in the time period to obtain a new concentration matrix; the specific calculation process is as follows: for any target square, from
Starting from the moment, reversely calculating the position of the central infinitesimal at the time t, wherein the concentration value of the square at the position at the time t is the concentration value of the target square at the time t
A concentration value at a time; wherein the pushing process is reversed
For a time interval, the backward shift is
Adding the sub-displacements to obtain; if the central micro element reaches the boundary square grid in the process, assuming that the central micro element does not move after reaching the vicinity of the boundary, only keeping the sub-displacement before reaching the boundary square grid;
multiplying each element in the density matrix by a coefficient
Obtaining a new concentration matrix after the attenuation process;
increase the current time
That is to say
And circularly executing the steps until t reaches the simulation end time.
9. The water body pollution diffusion simulation prediction method of any one of claims 1 to 4, further comprising: and carrying out visual display in a graphic and animation mode according to the simulation result data.
10. A water body pollution diffusion simulation prediction device based on concentration analysis is characterized by comprising: a processor and a computer readable storage medium storing a computer program which, when executed by the processor, performs the water body pollution diffusion simulation prediction method of any one of claims 1 to 9.
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