Hydrological and hydrodynamic process simulation method based on multiple GPUs

Abstract

The invention relates to the field of hydrological and hydrodynamic simulation, in particular to a hydrological and hydrodynamic process simulation method based on multiple GPUs, comprising the following steps: S1, acquiring basic data and pollutant data of a target area; s2, dividing the target region into a plurality of latticed sub-regions, and allocating a GPU for each sub-region; s3, calculating water flow data of each sub-region according to the basic data and the pollutant data, wherein the water flow data is used for representing the speed and the flow direction of water flow; s4, calculating the pollution concentration of each position at each moment according to the water flow data; according to the method, a feedback mechanism between bio-enrichment and biodegradation is considered, the concentration distribution of pollutants in the water body at different time points can be more accurately predicted, and the influence of a metabolic process and environmental factors in a living body can be better simulated, so that a simulation result is closer to an actual situation.

Description

Technical Field

[0001] The present invention relates to the field of hydrological and hydrodynamic simulation, and specifically to a method for simulating hydrological and hydrodynamic processes based on multiple GPUs. Background Art

[0002] When there are pollution sources in rivers, lakes or oceans, simulating the pollution range and the pollution concentration at each location using hydrological and hydrodynamic processes is the main technical means. Common simulation methods mainly rely on the simulation of initial conditions and boundary conditions, ignoring the significant impact of microbial activities (mainly microbial degradation and microbial enrichment) on pollutant concentration on the concentration distribution of pollutants in water bodies, resulting in the calculation accuracy of the pollution range and the pollution concentration at each location not meeting expectations, and further affecting the efficiency of sewage treatment in the later stage. Summary of the Invention

[0003] Aiming at the deficiencies of the prior art, the present invention provides a method for simulating hydrological and hydrodynamic processes based on multiple GPUs, which solves the technical problems in the above background art.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A method for simulating hydrological and hydrodynamic processes based on multiple GPUs includes the following steps:

[0006] S1. Obtain the basic data and pollutant data of the target area;

[0007] S2. Divide the target area into several grid-shaped sub-areas, and assign a GPU to each sub-area;

[0008] S3. Calculate the water flow data of each sub-area according to the basic data and pollutant data, where the water flow data is used to represent the speed and direction of the water flow;

[0009] S4. Calculate the pollution concentration at each location at each moment according to the water flow data.

[0010] Further, in step S1, the basic data includes topographic elevation, hydrological data, geological data, water body data and meteorological data; the pollutant data includes the initial concentration distribution and pollution source information;

[0011] The topographic elevation is used to describe the surface and underwater topography;

[0012] The geological data is used to describe the soil type and permeability coefficient;

[0013] The water body data includes the boundary conditions of the water body, the initial water level, the initial water depth and the flow velocity distribution;

[0014] The meteorological data includes wind speed, wind direction and temperature;

[0015] The initial concentration distribution represents the spatial distribution of pollutants at the initial moment;

[0016] The pollution source information includes the location, emission rate, and time series of the pollution source.

[0017] Further, in step S3, it specifically includes the following steps:

[0018] S31. Construct a coordinate system in the target area with the north-south direction and the east-west direction as the x-axis and y-axis respectively,

[0019] S32. Define the continuity equation;

[0020] S33. Solve the continuity equation according to the basic data to obtain the water depth distribution at the current moment;

[0021] S34. Calculate the first influence term used to represent other factors that will affect the water flow in the x-axis and y-axis directions and the second influence term

[0022] S35. Define the momentum equations of the water flow in the x-axis and y-axis directions;

[0023] S36. Solve the momentum equations according to the water depth distribution to obtain the water flow direction and velocity distribution at the next moment;

[0024] S37. Repeat the above steps to obtain the water flow data of each sub-region at each moment.

[0025] Further, in step S32, the expression of the continuity equation is:

[0026]

[0027] In the formula, θ represents the partial derivative; h represents the water depth; t represents the time; u represents the velocity component of the water flow along the x-axis; v represents the velocity component of the water flow along the y-axis; represents the change rate of the water depth with respect to time; represents the change rate of the product of the water flow velocity and the water depth along the x-axis direction; represents the change rate of the product of the water flow velocity and the water depth along the y-axis direction.

[0028] Further, in step S34, the first influence term and the second influence term both include the frictional force T b , the Coriolis force F c and the wind stress T W ;

[0029] Among them, the calculation formula of the frictional force T b is:

[0030]

[0031] Wherein, ρ represents the density of water; n represents the Manning roughness coefficient; the velocity vector u = (u x , u y );

[0032] The calculation formula of the Coriolis force F c is as follows:

[0033]

[0034] Wherein, m represents the mass density of water; Ω z = 2Ωsin(φ), where Ω represents the angular velocity vector of the earth's rotation; φ represents the dimension;

[0035] The calculation formula of the wind stress T W is as follows:

[0036]

[0037] Wherein, C d represents the wind drag coefficient; the wind speed vector W = (W x , W y );

[0038] The first influence term and the second influence term are the sum of the frictional force T b , the Coriolis force F c and the wind stress T W .

[0039] Furthermore, in step S35, the expressions of the momentum equation are respectively:

[0040]

[0041] Wherein, g represents the acceleration due to gravity.

[0042] Furthermore, in step S4, it specifically includes the following steps:

[0043] S41. According to the temperature at each moment, calculate the diffusion coefficient D of the pollutant, and its calculation formula is:

[0044]

[0045] Wherein, D0 represents the diffusion coefficient of the pollutant at the reference temperature; e represents the base of the natural logarithm; E a represents the minimum energy required for pollutant diffusion; R represents the ideal gas constant; T0 represents the reference temperature; T represents the actual temperature;

[0046] S42. Obtain the microbial data of the water body in the target area and calculate the biodegradation rate r(C, O2) and the bioaccumulation rate k bioen (C bio , C);

[0047] S43. Calculate the coupling coefficient α;

[0048] S44. Construct the coupling term f(C bio , C) according to the coupling coefficient α, and its calculation formula is:

[0049] f(C bio , C) = α × (C bio - C);

[0050] S45. Define the two-dimensional convection-diffusion equation according to the biodegradation rate r(C, O2), the bioaccumulation rate k bioen (C bio， c) and the coupling term f(C bio , C);

[0051] S46. Substitute the water flow data at each moment into the two-dimensional convection-diffusion equation and repeat the iteration to obtain the pollution concentration at each position at each moment and construct the concentration distribution map.

[0052] Further, in step S42, the calculation formulas for the biodegradation rate r(C, O2) and the bioaccumulation rate k bioen (C bio , C) are respectively:

[0053]

[0054] In the formula, μ max represents the maximum specific growth rate; K s represents the half-saturation constant; O2 represents the dissolved oxygen concentration of the water body in the target area; K O represents the oxygen half-saturation constant of the water body in the target area; k bioen represents the bioaccumulation rate constant; BAF represents the ratio of the pollutant concentration in the microorganism to the pollutant concentration in the water body; C represents the pollutant concentration of the water body in the target area; C bio represents the pollutant concentration in the microorganism.

[0055] Further, in step S43, the calculation formula for the coupling coefficient α is:

[0056]

[0057] In the formula, k uptake represents the speed of the microorganism absorbing pollutants; k excretion represents the speed of the microorganism discharging pollutants; Cbio , max represents the maximum pollutant concentration in the microorganism; C min represents the minimum pollutant concentration in the water body of the target area.

[0058] Furthermore, in step S45, the expression of the two-dimensional convection-diffusion equation is:

[0059]

[0060] wherein, r(C, O2) and k bioen (C bio , C) are the biodegradation rate and the bioaccumulation rate respectively.

[0061] Compared with the prior art, the present invention provides a method for simulating hydro-hydrodynamic processes based on multiple GPUs, having the following beneficial effects:

[0062] The present invention takes into account the feedback mechanism between bioaccumulation and biodegradation, can more accurately predict the pollutant concentration distribution in the water body at different time points, and can better simulate the metabolic process in the organism and the influence of environmental factors, making the simulation results closer to the actual situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The illustrative embodiments and descriptions thereof of the present application are used to explain the present application, and do not constitute an improper limitation to the present application. In the drawings:

[0064] Figure 1 is a flowchart of the steps of a method for simulating hydro-hydrodynamic processes based on multiple GPUs according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0065] In order to make the above objects, features and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the drawings and specific embodiments. Thereby, the implementation process of how the present application uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0066] Those of ordinary skill in the art can understand that all or part of the steps in the following embodiment methods can be completed by instructing relevant hardware through a program. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] Simulating the diffusion path and concentration change of pollutants in water bodies has important scientific significance and practical application value. For example, when accidents such as oil or chemical leakage occur in water bodies, through hydrological and hydrodynamic process simulation, the diffusion path of pollutants and the affected range of pollutants can be predicted, so as to carry out pollution treatment in the shortest time and avoid further spread of the pollution range. Therefore, as Figure 1 shown, the present invention proposes a method for simulating hydrological and hydrodynamic processes based on multiple GPUs, including the following steps:

[0068] S1. Obtain the basic data and pollutant data of the target area; specifically, if you want to calculate the pollution range of the pollution source, you need to calculate the water flow direction and water flow velocity of the corresponding water body, and you also need to obtain the soil diffusion degree at the corresponding position. Therefore, in step S1, the basic data includes topographic elevation, hydrological data, geological data, water body data and meteorological data; the pollutant data includes the initial concentration distribution and pollution source information; specifically, the topographic elevation is used to describe the surface and underwater terrain, which can be achieved through various means. Currently, the more common ones are drone aerial photography or lidar. Drone aerial photography uses software such as Pix4D and Agisofe Metashape for image stitching and 3D reconstruction to generate high-resolution topographic elevation; the hydrological data includes rainfall, evaporation and runoff, which can be directly obtained from weather stations or hydrological models; the geological data is used to describe the soil type and permeability coefficient, usually obtained from the geological survey bureau or relevant research institutions; the water body data includes the boundary conditions, initial water level, initial water depth and flow velocity distribution of the water body, which can be obtained from the geological survey bureau or relevant research institutions; the meteorological data includes wind speed, wind direction and temperature, which can be directly obtained from weather stations; the initial concentration distribution represents the spatial distribution of pollutants at the initial moment, which can be obtained through on-site monitoring or historical data; the pollution source information includes the location, emission rate and time series of the pollution source, which are determined by the environmental management department or on-site investigation.

[0069] S2. Divide the target area into several grid-shaped sub-areas, and allocate a GPU to each sub-area; specifically, since the hydrological and hydrodynamic model usually involves a large amount of calculations, especially when dealing with high-resolution terrain data and complex water flow dynamics, a multi-GPU system can parallel process these calculation tasks, greatly improving the simulation speed. In addition, multiple GPUs can optimize the usage efficiency of hardware resources and maximize the value of high-performance computing devices.

[0070] S3. Calculate the water flow data for each sub-region based on the basic data and pollutant data. The water flow data is used to represent the speed and direction of the water flow. Specifically, since the speed and direction of the water flow will directly affect the pollution range of the pollutants, when calculating the diffusion range of the pollutants, it is necessary to first calculate the speed and direction of the water flow in each sub-region. Therefore, in step S3, the following steps are specifically included:

[0071] S31. Construct a coordinate system in the target area with the north-south direction and the east-west direction as the x-axis and y-axis respectively.

[0072] S32. Define the continuity equation, and its expression is:

[0073]

[0074] In the formula, θ represents the partial derivative; h represents the water depth; t represents the time; u represents the velocity component of the water flow along the x-axis; v represents the velocity component of the water flow along the y-axis; represents the change rate of the water depth with time; represents the change rate of the product of the water flow velocity and the water depth along the x-axis direction; represents the change rate of the product of the water flow velocity and the water depth along the y-axis direction;

[0075] S33. Solve the continuity equation according to the basic data to obtain the water depth distribution at the current moment.

[0076] S34. Calculate the first influence term and the second influence term which are used to represent other factors that will affect the water flow in the x-axis and y-axis directions according to the basic data. Specifically, when the water flows converge, the collision of the water flows will cause an increase in the frictional force between the water flows. In addition, the inertial force caused by the rotation of the earth and the wind will both affect the water flow. Therefore, in step S34, the first influence term and the second influence term both include the frictional force T b , the Coriolis force F c and the wind stress T W ;

[0077] Among them, the calculation formula of the frictional force T b is:

[0078]

[0079] In the formula, ρ represents the density of water; n represents the Manning roughness coefficient; the velocity vector u = (u x , u y ); in the present invention, the value range of n is shown in Table 1;

[0080] Table 1:

[0081] Surface type Manning roughness coefficient n Concrete, smooth lining 0.010-0.015 Mortar lining 0.012-0.017 Natural rock 0.025-0.040 Natural gravel riverbed 0.025-0.035 Grassland 0.030-0.050 Forest cover 0.050-0.100 Tall grass or shrubs 0.060-0.090

[0082] Coriolis force F c The calculation formula is as follows:

[0083]

[0084] In the formula, m represents the mass density of water; Ω z = 2Ωsin(φ), where Ω represents the angular velocity vector of the earth's rotation; φ represents the dimension;

[0085] Wind stress T W The calculation formula is as follows:

[0086]

[0087] In the formula, C d represents the wind drag coefficient; the wind speed vector W = (W x , W y ); in the present invention, the value range of C d is shown in Table 2;

[0088] Table 2:

[0089]

[0090]

[0091] The first influence term and the second influence term are the sum of the frictional force T b , the Coriolis force F c and the wind stress T W .

[0092] S35. Define the momentum equations of the water flow in the x-axis and y-axis directions, and their expressions are respectively:

[0093]

[0094] In the formula, g represents the acceleration due to gravity;

[0095] S36. Solve the momentum equation according to the water depth distribution to obtain the water flow direction and velocity distribution at the next moment;

[0096] S37. Repeat the above steps to obtain the water flow data of each sub-region at each moment.

[0097] S4. Calculate the pollution concentration at each position at each moment according to the water flow data; specifically, since the pollution concentration will be affected by microbial degradation, therefore, in step S4, the following steps are specifically included:

[0098] S41. According to the temperature at each moment, calculate the diffusion coefficient D of the pollutant. The calculation formula is as follows:

[0099]

[0100] In the formula, D0 represents the diffusion coefficient of the pollutant at the reference temperature; e represents the base of the natural logarithm; E a represents the minimum energy required for pollutant diffusion; R represents the ideal gas constant; T0 represents the reference temperature; T represents the actual temperature; in the present invention, D0 is obtained through experiments according to the actual type of the corresponding pollutant; R is 8.314; T0 is 25; E a The value of needs to be determined according to the actual substance, as shown in Table 3;

[0101] Table 3:

[0102]

[0103]

[0104] S42. Obtain the microbial data of the water body in the target area and calculate the biodegradation rate r(C, O2) and the bioaccumulation rate k bioen (C bio , C); specifically, in step S42, the calculation formulas for the biodegradation rate r(C, O2) and the bioaccumulation rate k bioen (C bio , C) are respectively:

[0105]

[0106] In the formula, μ max represents the maximum specific growth rate; K s represents the half-saturation constant; O2 represents the dissolved oxygen concentration of the water body in the target area; K O represents the oxygen half-saturation constant of the water body in the target area; k bioen represents the bioaccumulation rate constant; BAF represents the ratio of the pollutant concentration in the microorganism to the pollutant concentration in the water body; C represents the pollutant concentration of the water body in the target area; C bio represents the pollutant concentration in the microorganism; in the present invention, μ max , K s , K O and O2 can all be obtained through laboratory experiments; C bio can be determined by chemical analysis of biological samples; C can be determined by collecting water samples and performing chemical analysis;

[0107] S43. Calculate the coupling coefficient α. The calculation formula is as follows:

[0108]

[0109] In the formula, k uptake represents the rate at which microorganisms absorb pollutants; k excretion represents the rate at which microorganisms discharge pollutants; C bio , max represents the maximum pollutant concentration in the microorganisms; C min represents the minimum pollutant concentration in the water body of the target area; in the present invention, k uptake and k excretion are 0.05 and 0.02 respectively; C bio，max and C min are obtained by measurement;

[0110] S44. Construct a coupling term f(C bio , C) according to the coupling coefficient α, and its calculation formula is:

[0111] f(C bio , C) = α × (C bio - C);

[0112] S45. Define a two-dimensional convection-diffusion equation according to the biodegradation rate r(C, O2), the bioaccumulation rate k bioen (C bio , C) and the coupling term f(C bio , C), and its expression is:

[0113]

[0114] In the formula, r(C, O2) and k bioen (C bio , C) are the biodegradation rate and the bioaccumulation rate respectively;

[0115] S46. Substitute the water flow data at each moment into the two-dimensional convection-diffusion equation and repeat the iteration to obtain the pollution concentration at each position at each moment.

[0116] Common methods for calculating the pollution concentration at each position in the water body only simulate based on the initial conditions and boundary conditions, without considering the influence of bioaccumulation and biodegradation on the pollutant concentration. In addition, common calculation methods also ignore the metabolic process in microorganisms and its influence on the pollutant concentration, so the simulation results will deviate. The present invention takes into account the feedback mechanism between bioaccumulation and biodegradation, can more accurately predict the distribution of pollutant concentration in the water body at different time points, and can better simulate the metabolic process in organisms and the influence of environmental factors, making the simulation results closer to the actual situation, so as to facilitate formulating a pollution treatment plan based on it.

[0117] The above embodiments have introduced the present invention in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation on the present invention.

Claims

1. A method for simulating hydrological and hydrodynamic processes based on multiple GPUs, characterized in that It includes the following steps: S1. Obtain the basic data and pollutant data of the target area; S2. Divide the target area into several grid-shaped sub-areas and allocate a GPU to each sub-area; S3. Calculate the water flow data of each sub-area according to the basic data and pollutant data, where the water flow data is used to represent the velocity and direction of the water flow; S4. Calculate the pollution concentration at each position at each moment according to the water flow data.

2. The hydrological and hydrodynamic process simulation method according to claim 1, wherein In step S1, the basic data includes terrain elevation, hydrological data, geological data, water body data, and meteorological data; the pollutant data includes the initial concentration distribution and pollution source information; The terrain elevation is used to describe the surface and underwater terrain; The geological data is used to describe the soil type and permeability coefficient; The water body data includes the boundary conditions of the water body, initial water level, initial water depth, and velocity distribution; The meteorological data includes wind speed, wind direction, and temperature; The initial concentration distribution represents the spatial distribution of pollutants at the initial moment; The pollution source information includes the location, emission rate, and time series of the pollution source.

3. The hydrological and hydrodynamic process simulation method according to claim 1, characterized in that In step S3, it specifically includes the following steps: S31. Construct a coordinate system in the target area with the north-south direction and east-west direction as the x-axis and y-axis respectively, S32. Define the continuity equation; S33. Solve the continuity equation according to the basic data to obtain the water depth distribution at the current moment; S34. Calculate a first influence term used to represent other factors that will affect the water flow in the x-axis and y-axis directions based on the basic data and a second influence term S35. Define the momentum equations of the water flow in the x-axis and y-axis directions; S36. Solve the momentum equations according to the water depth distribution to obtain the water flow direction and velocity distribution at the next moment; S37. Repeat the above steps to obtain the water flow data of each sub-area at each moment.

4. The hydrological and hydrodynamic process simulation method according to claim 3, characterized in that, In step S32, the expression of the continuity equation is: In the formula, θ represents the partial derivative; h represents the water depth; t represents the time; u represents the velocity component of the water flow along the x-axis; v represents the velocity component of the water flow along the y-axis; represents the rate of change of the water depth with respect to time; represents the rate of change of the product of the water flow velocity and the water depth along the x-axis; represents the rate of change of the product of the water flow velocity and the water depth along the y-axis.

5. The hydrological and hydrodynamic process simulation method according to claim 3, characterized in that In step S34, the first influencing item and the second influencing item both include the frictional force T b , the Coriolis force F c and the wind stress T W ; Among them, the frictional force T b has the following calculation formula: where ρ represents the density of water; n represents the Manning roughness coefficient; the flow velocity vector u = (u x , u y ); Coriolis force F c The calculation formula is as follows: where m represents the mass density of water; Ω z = 2Ωsin(φ), where Ω represents the angular velocity vector of the Earth's rotation; φ represents the latitude; Wind stress T W The calculation formula is as follows: where C d represents the wind drag coefficient; the wind speed vector W = (W x , W y ); The first influencing term and the second influencing term are the sum of the frictional force T b , the Coriolis force F c and the wind stress T W .

6. The hydrological and hydrodynamic process simulation method according to claim 3, wherein In step S35, the expressions of the momentum equations are respectively: In the formula, g represents the acceleration due to gravity.

7. The hydrological and hydrodynamic process simulation method according to claim 1, characterized in that, In step S4, it specifically includes the following steps: S41. According to the temperature at each moment, calculate the diffusion coefficient D of the pollutant, and its calculation formula is: In the formula, D0 represents the diffusion coefficient of the pollutant at the reference temperature; e represents the base of the natural logarithm; E a represents the minimum energy required for pollutant diffusion; R represents the ideal gas constant; T0 represents the reference temperature; T represents the actual temperature; S42. Obtain the microbial data of the water body in the target area and calculate the biodegradation rate r(C, O2) and the bioaccumulation rate k bioen (C bio , C); S43. Calculate the coupling coefficient α; S44. Construct a coupling term f(C bio , C) according to the coupling coefficient α, and its calculation formula is: f(C bio , C) = α × (C bio - C); S45. According to the biodegradation rate r(C, O2), the bioaccumulation rate K bione (C bio , C) and the coupling term f(C bio , C) and define a two-dimensional convection-diffusion equation; S46. Substitute the water flow data at each moment into the two-dimensional convection-diffusion equation and repeat the iteration to obtain the pollution concentration at each position at each moment and construct a concentration distribution map.

8. The hydrological and hydrodynamic process simulation method according to claim 7, characterized in that In step S42, the biodegradation rate r(C, O2) and the bioaccumulation rate k bioen (C bio , C) are calculated by the following formulas respectively: where μ max represents the maximum specific growth rate; K s represents the half-saturation constant; O2 represents the dissolved oxygen concentration of the water body in the target area; K O represents the oxygen half-saturation constant of the water body in the target area; k bioen represents the bioconcentration rate constant; BAF represents the ratio of the pollutant concentration in the microorganism to the pollutant concentration in the water body; C represents the pollutant concentration of the water body in the target area; C bio represents the pollutant concentration in the microorganism.

9. The hydrological and hydrodynamic process simulation method according to claim 7, wherein In step S43, the calculation formula of the coupling coefficient α is: where k uptake represents the rate at which microorganisms absorb pollutants; k excretion represents the rate at which microorganisms excrete pollutants; C bio，max represents the maximum pollutant concentration in microorganisms; C min represents the minimum pollutant concentration in the water body of the target area.

10. The hydrological and hydrodynamic process simulation method according to claim 7, characterized in that In step S45, the expression of the two-dimensional convection-diffusion equation is: where r(C, O2) and k bioen (C bio , C) are the biodegradation rate and the bioaccumulation rate, respectively.

Images