Nuclear pollutant ocean traceability system and method

Abstract

The invention discloses a nuclear pollutant ocean traceability system and method, and the system comprises a traceability system body, the traceability system body comprises a service platform, a visual platform, a sub-platform, an information flow platform and a software configuration platform, the service platform carries out information management in a front and rear end separation manner, and the visual platform displays a traceability result. The sub-platforms realize system management and basic configuration functions required by business operation, the information flow platform carries out simulation forecast of the transportation process of nuclear pollutants in the atmospheric ocean based on an obtained atmospheric ocean numerical forecasting system forecast result, a simulation result enters visual software, and the simulation result is displayed on the information flow platform. On the basis of forecast data of a global ocean numerical forecasting system, positions and time of nuclear pollutants found in an ocean environment and a backward trajectory clustering analysis method, an ocean nuclear pollutant traceability subsystem is developed, and the subsystem can realize traceability of a nuclear accident occurrence place according to the positions and time input by a user.

Description

A marine source tracing system and method for nuclear pollutants Technical Field

[0001] This invention relates to the field of nuclear pollutant source tracing technology, specifically to a nuclear pollutant marine source tracing system and method. Background Technology

[0002] Pollution source tracing technology refers to the technical means of tracing, finding, and identifying pollution sources by simulating and analyzing the transmission, diffusion, and evolution of environmental pollutants, as well as identifying and characterizing certain characteristics of environmental pollutants. It helps us better understand the types, locations, and impact ranges of pollution sources, providing scientific basis and technical support for environmental protection and governance. Among these technologies, marine pollution source tracing is the foundation for determining the responsible parties and winning the battle for comprehensive governance of key marine areas.

[0003] Numerous marine pollutants exist, with nuclear contaminants being one of them. Firstly, the primary source of nuclear-contaminated water and other nuclear pollutants is nuclear power plants. During nuclear power generation, large amounts of cooling water are used to lower the reactor temperature. This cooling water, upon contact with the reactor, becomes contaminated with radioactive materials, thus becoming nuclear-contaminated water. Furthermore, nuclear weapons tests and nuclear accidents can also lead to the generation of nuclear-contaminated water. The discharge of nuclear-contaminated water is a major concern. Generally, nuclear power plants employ multiple protective measures to control the discharge of nuclear-contaminated water because it contains radioactive and toxic substances such as uranium, actinium, and plutonium, which can contaminate... Seawater directly poisons marine life and ecosystems, damaging the integrity of the marine ecosystem. Radioactive materials entering the ocean are ingested by marine organisms and then transmitted to all levels of the food chain. These radioactive materials may interfere with the reproductive and developmental processes of marine organisms, leading to decreased reproductive capacity, genetic mutations, or abnormalities. Therefore, measures should be taken to effectively prevent the direct discharge of nuclear wastewater into the ocean, and the treatment and disposal of nuclear waste should be strengthened to protect the stability and integrity of the marine ecosystem. However, nuclear leakage accidents are still unavoidable. In current technology, people generally use a nuclear pollutant marine source tracing system to trace the source of nuclear leakage accidents.

[0004] However, traditional marine tracing systems for nuclear contaminants have the following drawbacks: they only trace the source of nuclear contamination accidents and the tracing content is limited to the address, resulting in a single tracing result that cannot meet people's needs. Summary of the Invention

[0005] The purpose of this invention is to provide a marine source tracing system and method for nuclear pollutants, in order to solve the problems of the traditional marine source tracing system for nuclear pollutants mentioned in the background art, which only traces the source of nuclear pollution accidents and only traces the address, resulting in a single source tracing result that cannot meet people's needs.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a marine source tracing system for nuclear pollutants, comprising a source tracing system body, which includes a service platform, a visualization platform, a sub-platform, an information flow platform, and a software configuration platform. The service platform adopts a front-end and back-end separation approach for information management. The visualization platform displays the source tracing results. The sub-platform implements the system management and basic configuration functions required for business operation. The information flow platform relies on the forecast results obtained from the atmospheric and oceanic numerical forecasting system to conduct simulation forecasts of the transport process of nuclear pollutants in the atmosphere and ocean. The simulation results are entered into the visualization software. The software configuration platform realizes the project objectives of marine nuclear source tracing and historical nuclear observation information query. The service platform includes a service back-end module and a product creation module. The service back-end module includes a Python language unit, a data analysis and processing unit, a format conversion unit, and a classification and organization unit. The visualization platform includes a visualization expression module and an interface display module.

[0007] As a preferred technical solution of the present invention, the service backend module collects, organizes and temporarily stores the data based on the obtained complete data, which facilitates the reuse of the data and is also a key step to speed up the data processing response, laying a solid foundation for data visualization. The product creation module realizes the front-end drawing for display visualization.

[0008] As a preferred technical solution of the present invention, the Python language unit is based on the Python language, and the data analysis and processing unit fully utilizes the advantages of the NumPy, Pandas, and SciPy data analysis and processing libraries to design a data fast processing and storage analysis module. Based on the existing pattern data and observation data, the relevant data is classified and processed. The format conversion unit needs to perform a unified standard format conversion on the existing observation data and pattern data for subsequent use and display on the platform because the existing data are from inconsistent sources and the standards of all sources are not the same. The classification and sorting unit classifies and sorts the data to realize the data storage operation.

[0009] As a preferred embodiment of the present invention, the data analysis and processing unit includes a NumPy database, a Pandas database, and a SciPy database. The NumPy database is designed for rapid data processing and input into the NumPy database analysis module, where relevant data is classified based on existing pattern data and observation data. The Pandas database is designed for rapid data processing and input into the Pandas database analysis module, where relevant data is classified based on existing pattern data and observation data. The SciPy database is designed for rapid data processing and input into the SciPy database analysis module, where relevant data is classified based on existing pattern data and observation data.

[0010] As a preferred technical solution of the present invention, the product production module includes a canvas unit, a parameter setting unit, and a data extraction unit. The canvas unit is built on canvas technology and uses canvas calculation to realize front-end drawing for visualization. The parameter setting unit sets parameters, and the visualization service platform front end will send a request to the service platform back-end data processing system. The data extraction unit extracts data from specified elements in a specified area, at a specified time, and at a specified level, and performs rapid visualization drawing and display on the service platform front end.

[0011] As a preferred technical solution of the present invention, the data extraction unit includes a specified area extraction block, a specified time extraction block, and a specified level extraction block. The specified area extraction block extracts data from a specified area and performs rapid visualization drawing and display on the front end of the service platform. The specified time extraction block extracts data from specified elements at a specified time and performs rapid visualization drawing and display on the front end of the service platform. The specified level extraction block extracts data from specified elements at a specified level and performs rapid visualization drawing and display on the front end of the service platform.

[0012] As a preferred technical solution of the present invention, the visualization expression module includes contour lines, color-filled maps, profiles, and time series, which can meet the visualization display of atmospheric nuclear pollutant diffusion products (0-168 hours globally), marine nuclear pollutant diffusion products (0-120 hours globally), diffusion trajectories, diffusion concentrations, and cumulative sedimentation on the land surface and in the sea, as well as display of information related to marine source tracing of pollutants.

[0013] As a preferred technical solution of the present invention, the visualization expression module includes contour lines, color-filled plots, profiles, and time series units. The contour lines express the marine source tracing of pollutants using contour lines, the color-filled plots express the marine source tracing of pollutants using color-filled plots, the profiles express the marine source tracing of pollutants using profiles, and the time series units express the marine source tracing of pollutants using time series methods.

[0014] As a preferred embodiment of the present invention, the sub-platform includes a user management module, a parameter setting module, and a file management module. The user management module manages users of the traceability system, the parameter setting module sets relevant parameters of the traceability system, and the file management module manages files within the traceability system.

[0015] As a preferred embodiment of the present invention, the information flow platform includes an external support module, a data collection module, a model system module, a data input module, and a source tracing output module. The external support module relies on an operational marine numerical weather prediction system. The data collection module collects historical typical hydrological and meteorological observation data, atmospheric and marine nuclear material observation data, historical marine and atmospheric numerical simulation data, and marine and atmospheric numerical weather prediction data. The model system module is divided into a radioactive material model and a marine radioactive material transport model. The data input module inputs accident-related data, and the source tracing output module outputs source tracing-related data.

[0016] As a preferred technical solution of the present invention, the software configuration platform includes a data preprocessing module, a marine nuclear source tracing module, and a historical nuclear information query module. The data preprocessing module preprocesses the values ​​input to the source tracing system. The marine nuclear source tracing module can trace the nuclear pollution source in reverse and has a visual operation function. By inputting the accident point and the total amount of nuclear leakage, the system can complete the overall forecast. The historical nuclear information query module queries historical nuclear pollution information.

[0017] As a preferred embodiment of the present invention, the interface display module includes an event name unit, a location information unit, an observation time unit, a source tracing timeliness unit, a model calculation unit, a source tracing trajectory unit, a particle count unit, and a real-time monitoring unit. The event name unit names the nuclear leak event, the location information unit displays the longitude and latitude of the nuclear leak, the observation time unit displays the observed time, the source tracing timeliness unit displays the source tracing timeliness, the model calculation unit performs model calculations based on the data, the source tracing trajectory unit traces the source of nuclear contamination, the particle count unit displays the number of particles generated by nuclear contamination, and the real-time monitoring unit monitors the nuclear contamination process in real time.

[0018] This invention discloses a method for tracing the marine source of nuclear pollutants, comprising the following steps: Step 1, Data Input: Inputting past forecast data from the atmospheric and marine environmental numerical forecasting system, inputting acquired nuclear pollutant data, and inputting cluster analysis data of backward trajectories based on the atmospheric and marine particle model; Step 2, Formula Input: Inputting particle motion formulas under different conditions; Step 3, Model Construction: Constructing a marine nuclear pollutant source tracing model. The model can, based on the location and time of the first detected nuclear pollutant, begin deploying backward-tracing particles at the initial location, acquire past atmospheric and marine numerical forecast data, begin backward-tracing, and, based on the known location of nuclear facilities, estimate nuclear contamination accidents. Location of occurrence; Step 4, Start-up mode: By inputting the location of nuclear pollutants monitored (cesium-137, strontium-90, iodine-131) and the time of initial monitoring, and using the forecast results of wind field, flow field, temperature, salinity, and density from the accessed global atmospheric and oceanic numerical forecasting system, the entire atmospheric and oceanic nuclear pollutant source tracing subsystem is started; Step 5, Location determination: The generated source tracing path dataset is imported into the product production, integration, and operationalization subsystem to complete the location of the nuclear facility where the nuclear pollutant leak occurred; Step 6, Accident simulation: The product further conducts simulations of nuclear pollution leak accidents; Step 7, Marine nuclear source tracing and treatment: Source tracing and treatment of nuclear pollutants in the ocean is carried out.

[0019] As a preferred embodiment of the present invention, the motion formula in step two is specifically that the motion of the particle is controlled by the following equation: The formula can be solved using Euler integrals or Runge-Kutta integrals. For particle position, The random motion velocity caused by turbulence, Let be the velocity of the drifting particle. The velocity of the horizontally moving particle is . , , , These represent the three components of wind speed. These data are output in real time by the forecasting system. The random motion caused by turbulent diffusion is usually calculated using the "random walk" technique, and its velocity can be expressed as: , The horizontal or vertical diffusion coefficient is given. The horizontal diffusion coefficient can be calculated using the Smagorinsky formula based on the wind field and seawater velocity.

[0020] As a preferred technical solution of the present invention, the specific process of the source tracing process in step seven is as follows: Access the webpage: http: / / 192.168.5.60:8000 / , create a new kernel source tracing event on the front end and input relevant parameters, access the Linux server: 192.168.5.60; access the directory: Open the file `OcnBwdCaselists.json` in ` / home / hks / HKS / NuclearNM / model` to see the parameters displayed as a Python dictionary. Submit the "Model Calculation" button for marine nuclear traceability on the front end. Check the system monitoring and, based on the system monitoring progress, view the corresponding data results in the backend. Navigate to the directory ` / home / hks / data / DATA_NuclearNM / ocndata` to view the system's preprocessing results. Navigate to the directory ` / home / hks / data / DATA_NuclearNM / model_result / ocn / CasesBWD / qingdao / output` to view the model-generated data `20230201_all.dat`. Navigate to the directory ` / home / hks / data / DATA_NuclearNM / model_result / ocn / CasesBWD / qingdao / output` to view the system's post-processing result data `20230201_end_sta.dat`.

[0021] Compared with the prior art, the beneficial effects of the present invention are: based on the forecast data of the global ocean numerical forecasting system, for the location and time of nuclear pollutants found in the marine environment, a marine nuclear pollutant source tracing subsystem is developed based on the backward trajectory clustering analysis method. The subsystem can realize the source tracing of the nuclear accident site according to the location and time input by the user. Attached Figure Description

[0022] Figure 1 is a schematic diagram of the structure of the traceability system body of the present invention; Figure 2 is a schematic diagram of the structure of the service platform of the present invention; Figure 3 is a schematic diagram of the structure of the service backend module of the present invention; Figure 4 is a schematic diagram of the structure of the data analysis and processing unit of the present invention; Figure 5 is a schematic diagram of the structure of the product production module of the present invention; Figure 6 is a schematic diagram of the structure of the data extraction unit of the present invention; Figure 7 is a schematic diagram of the structure of the visualization platform of the present invention; Figure 8 is a schematic diagram of the structure of the visualization expression module of the present invention; Figure 9 is a schematic diagram of the structure of the sub-platform of the present invention; Figure 10 is a schematic diagram of the structure of the information flow platform of the present invention; Figure 11 is a schematic diagram of the structure of the software configuration platform of the present invention; Figure 12 is a schematic diagram of the structure of the interface display module of the present invention; Figure 13 is a schematic diagram of the creation of marine nuclear traceability and input parameters of the present invention; Figure 14 is a schematic diagram of the backend saving file of the creation of marine nuclear traceability and input parameters of the present invention; Figure 15 is a schematic diagram of the submission of the "model calculation" of marine nuclear traceability of the present invention; Figure 16 is a schematic diagram of the monitoring of the marine nuclear traceability mode system of the present invention; Figure 17 is a schematic diagram of the corresponding data of the marine nuclear traceability mode data monitoring of the present invention; Figure 18 is a flowchart of the present invention.

[0023] In the diagram: 1. Traceability System Main Body; 2. Service Platform; 21. Service Backend Module; 211. Python Language Unit; 212. Data Analysis and Processing Unit; 2121. NumPy Database; 2122. Pandas Database; 2123. SciPy Database; 213. Format Conversion Unit; 214. Classification and Organization Unit; 22. Product Creation Module; 221. Canvas Unit; 222. Parameter Setting Unit; 223. Data Extraction Unit; 2231. Extraction Block for Specified Area; 2232. Extraction Block for Specified Time; 2233. Extraction Block for Specified Level; 3. Visualization Platform; 31. Visualization Expression Module; 311. Contour Line Unit; 312. Color Fill Map Unit; 313. Section 314. Surface Unit; 32. Time Series Unit; 32. Interface Display Module; 321. Event Name Unit; 322. Location Information Unit; 323. Observation Time Unit; 324. Source Tracing Timeliness Unit; 325. Model Calculation Unit; 326. Source Tracing Trajectory Unit; 327. Particle Number Unit; 328. Real-time Monitoring Unit; 4. Sub-platform; 41. User Management Module; 42. Parameter Setting Module; 43. File Management Module; 5. Information Flow Platform; 51. External Support Module; 52. Data Collection Module; 53. Model System Module; 54. Data Input Module; 55. Source Tracing Output Module; 6. Software Configuration Platform; 61. Data Preprocessing Module; 62. Marine Nuclear Source Tracing Module; 63. Historical Nuclear Information Query Module. Detailed Implementation

[0024] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0025] Please refer to Figures 1-18. This invention provides a marine source tracing system for nuclear pollutants, including a source tracing system body 1. The source tracing system body 1 includes a service platform 2, a visualization platform 3, a sub-platform 4, an information flow platform 5, and a software configuration platform 6. The service platform 2 adopts a front-end and back-end separation approach for information management. The visualization platform 3 displays the source tracing results. The sub-platform 4 implements the system management and basic configuration functions required for business operation. The information flow platform 5 relies on the forecast results obtained from the atmospheric and oceanic numerical forecasting system to conduct simulation forecasts of the transport process of nuclear pollutants in the atmosphere and ocean. The simulation results are entered into the visualization software. The software configuration platform 6 realizes the achievement of the project task objectives of marine nuclear source tracing and historical nuclear observation information query. The service platform 2 includes a service back-end module 21 and a product production module 22. The service back-end module 21 includes a Python language unit 211, a data analysis and processing unit 212, a format conversion unit 213, and a classification and organization unit 214. The visualization platform 3 includes a visualization expression module 31 and an interface display module 32.

[0026] Based on the complete data obtained, the service backend module 21 collects, organizes, and temporarily stores the data to facilitate data reuse. This is also a key step in accelerating data processing response and laying a solid foundation for data visualization. The product creation module 22 realizes the front-end drawing for displaying visualization.

[0027] The Python language unit 211 is based on the Python language. The data analysis and processing unit 212 fully utilizes the advantages of the NumPy, Pandas, and SciPy data analysis and processing libraries to design a fast data processing and storage analysis module. Based on existing pattern data and observation data, it classifies and processes relevant data. The format conversion unit 213, due to the inconsistent sources of existing data and the different standards of all sources, needs to perform a unified standard format conversion on the existing observation data and pattern data for subsequent use and display on the platform. The classification and organization unit 214 classifies and organizes the data to realize the data storage operation.

[0028] The data analysis and processing unit 212 includes a NumPy database 2121, a Pandas database 2122, and a SciPy database 2123. The NumPy database 2121 is designed for rapid data processing into the NumPy database analysis module, which classifies and processes relevant data based on existing pattern data and observation data. The Pandas database 2122 is designed for rapid data processing into the Pandas database analysis module, which classifies and processes relevant data based on existing pattern data and observation data. The SciPy database 2123 is designed for rapid data processing into the SciPy database analysis module, which classifies and processes relevant data based on existing pattern data and observation data.

[0029] Product creation module 22 includes canvas unit 221, parameter setting unit 222, and data extraction unit 223. Canvas unit 221 is built on canvas technology and uses canvas calculation to realize front-end drawing for visualization. Parameter setting unit 222 sets parameters, and the visualization service platform front end will send a request to the service platform back-end data processing system. Data extraction unit 223 extracts data from specified elements in specified areas, specified times, and specified levels, and performs rapid visualization drawing and display on the service platform front end.

[0030] The data extraction unit 223 includes a specified area extraction block 2231, a specified time extraction block 2232, and a specified level extraction block 2233. The specified area extraction block 2231 extracts data from a specified area and performs rapid visualization plotting and display on the front end of the service platform. The specified time extraction block 2232 extracts data from specified elements at a specified time and performs rapid visualization plotting and display on the front end of the service platform. The specified level extraction block 2233 extracts data from specified elements at a specified level and performs rapid visualization plotting and display on the front end of the service platform.

[0031] The visualization module 31 includes contour lines, color-filled maps, profiles, and time series, which meet the visualization display needs of atmospheric nuclear pollutant diffusion products (0-168 hours globally), marine nuclear pollutant diffusion products (0-120 hours globally), diffusion trajectories, diffusion concentrations, and cumulative surface and marine sedimentation. The interface display module 32 displays information related to marine source tracing of pollutants.

[0032] The visualization module 31 includes contour line units 311, color-filled map units 312, profile units 313, and time series units 314. Contour line units 311 express the marine source of pollutants through contour lines, color-filled map units 312 express the marine source of pollutants through color-filled maps, profile units 313 express the marine source of pollutants through profiles, and time series units 314 express the marine source of pollutants through time series.

[0033] Sub-platform 4 includes a user management module 41, a parameter setting module 42, and a file management module 43. The user management module 41 manages users of the traceability system body 1, the parameter setting module 42 sets relevant parameters of the traceability system body 1, and the file management module 43 manages files within the traceability system body 1.

[0034] The information flow platform 5 includes an external support module 51, a data collection module 52, a model system module 53, a data input module 54, and a source tracing output module 55. The external support module 51 relies on the operational marine numerical weather prediction system. The data collection module 52 collects historical typical hydrological and meteorological observation data, atmospheric and marine nuclear material observation data, historical marine and atmospheric numerical simulation data, and marine and atmospheric numerical weather prediction data. The model system module 53 is divided into a radioactive material model and a marine radioactive material transport model. The data input module 54 inputs accident-related data, and the source tracing output module 55 outputs source tracing-related data.

[0035] The software configuration platform 6 includes a data preprocessing module 61, a marine nuclear source tracing module 62, and a historical nuclear information query module 63. The data preprocessing module 61 preprocesses the values ​​input to the source tracing system body 1. The marine nuclear source tracing module 62 can trace the source of nuclear pollution in reverse and has a visual operation function. By inputting the accident point and the total amount of nuclear leakage, the overall forecast can be completed. The historical nuclear information query module 63 can query historical information on nuclear pollution.

[0036] The interface display module 32 includes an event name unit 321, a location information unit 322, an observation time unit 323, a source tracing time unit 324, a model calculation unit 325, a source tracing trajectory unit 326, a particle count unit 327, and a real-time monitoring unit 328. The event name unit 321 names the nuclear leak event, the location information unit 322 displays the latitude and longitude of the nuclear leak, the observation time unit 323 displays the observed time, the source tracing time unit 324 displays the source tracing time length, the model calculation unit 325 performs model calculations based on the data, the source tracing trajectory unit 326 traces the nuclear contamination trajectory, the particle count unit 327 displays the number of particles generated by the nuclear contamination, and the real-time monitoring unit 328 monitors the nuclear contamination process in real time.

[0037] This invention discloses a method for tracing the marine source of nuclear pollutants, comprising the following steps: Step 1, Data Input: Inputting past forecast data from the atmospheric and marine environmental numerical forecasting system, inputting acquired nuclear pollutant data, and inputting cluster analysis data of backward trajectories based on the atmospheric and marine particle model; Step 2, Formula Input: Inputting particle motion formulas under different conditions; Step 3, Model Construction: Constructing a marine nuclear pollutant source tracing model. The model can, based on the location and time of the first detected nuclear pollutant, begin deploying backward-tracing particles at the initial location, acquire past atmospheric and marine numerical forecast data, begin backward-tracing, and, based on the known location of nuclear facilities, estimate nuclear contamination accidents. Location of occurrence; Step 4, Start-up mode: By inputting the location of nuclear pollutants monitored (cesium-137, strontium-90, iodine-131) and the time of initial monitoring, and using the forecast results of wind field, flow field, temperature, salinity, and density from the accessed global atmospheric and oceanic numerical forecasting system, the entire atmospheric and oceanic nuclear pollutant source tracing subsystem is started; Step 5, Location determination: The generated source tracing path dataset is imported into the product production, integration, and operationalization subsystem to complete the location of the nuclear facility where the nuclear pollutant leak occurred; Step 6, Accident simulation: The product further conducts simulations of nuclear pollution leak accidents; Step 7, Marine nuclear source tracing and treatment: Source tracing and treatment of nuclear pollutants in the ocean is carried out.

[0038] In step two, the motion formula specifically states that the particle's motion is controlled by the following equations: The formula can be solved using Euler integrals or Runge-Kutta integrals. For particle position, The random motion velocity caused by turbulence, Let be the velocity of the drifting particle. The velocity of the horizontally moving particle is . , , , These represent the three components of wind speed. These data are output in real time by the forecasting system. The random motion caused by turbulent diffusion is usually calculated using the "random walk" technique, and its velocity can be expressed as: , The horizontal or vertical diffusion coefficient is given. The horizontal diffusion coefficient can be calculated using the Smagorinsky formula based on the wind field and seawater velocity.

[0039] The specific process of source tracing in step seven is as follows: Access the webpage: http: / / 192.168.5.60:8000 / , create a new kernel source tracing event on the front end and input relevant parameters, access the Linux server: 192.168.5.60; enter the directory: Open the file `OcnBwdCaselists.json` in ` / home / hks / HKS / NuclearNM / model` to see the parameters displayed as a Python dictionary. Submit the "Model Calculation" button for marine nuclear traceability on the front end. Check the system monitoring and, based on the system monitoring progress, view the corresponding data results in the backend. Navigate to the directory ` / home / hks / data / DATA_NuclearNM / ocndata` to view the system's preprocessing results. Navigate to the directory ` / home / hks / data / DATA_NuclearNM / model_result / ocn / CasesBWD / qingdao / output` to view the model-generated data `20230201_all.dat`. Navigate to the directory ` / home / hks / data / DATA_NuclearNM / model_result / ocn / CasesBWD / qingdao / output` to view the system's post-processing result data `20230201_end_sta.dat`.

[0040] In this invention, the following steps are taken: inputting past forecast data from the atmospheric and oceanic environmental numerical forecasting system, inputting acquired nuclear pollutant data, and inputting cluster analysis data of backward trajectories based on the atmospheric and oceanic particle model; inputting particle motion formulas under different conditions; constructing a marine nuclear pollutant source tracing model, which can, based on the location and time of the first detected nuclear pollutant, begin deploying backward tracing particles at the initial location, acquire past atmospheric and oceanic numerical forecast data, begin backward tracing, and, based on the known location of nuclear facilities, estimate the location of the nuclear pollution accident; inputting the locations of the detected nuclear pollutants (cesium-137, strontium-90, iodine-131) and the time of the first detection, and using the forecast results of wind field, flow field, temperature, salinity, and density from the accessed global atmospheric and oceanic numerical forecasting system, starting the entire atmospheric and oceanic nuclear pollutant source tracing subsystem; importing the resulting source tracing path dataset into the product production, integration, and operationalization subsystem to complete the location of the nuclear facility where the nuclear pollutant leak occurred; further simulating nuclear pollution leak accidents; and performing source tracing processing on marine nuclear pollutants.

[0041] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A marine source tracing system for nuclear pollutants, comprising a source tracing system body (1), characterized in that: The source tracing system body (1) includes a service platform (2), a visualization platform (3), a sub-platform (4), an information flow platform (5), and a software configuration platform (6). The service platform (2) adopts a front-end and back-end separation approach for information management. The visualization platform (3) displays the source tracing results. The sub-platform (4) implements the system management and basic configuration functions required for business operation. The information flow platform (5) relies on the forecast results of the obtained atmospheric and oceanic numerical forecasting system to carry out simulation forecasts of the transport process of nuclear pollutants in the atmosphere and ocean. The simulation results are entered into the visualization software. The software configuration platform (6) realizes the achievement of the project task objectives of marine nuclear source tracing and historical nuclear observation information query. The service platform (2) includes a service back-end module (21) and a product production module (22). The service back-end module (21) includes a Python language unit (211), a data analysis and processing unit (212), a format conversion unit (213), and a classification and organization unit (214). The visualization platform (3) includes a visualization expression module (31) and an interface display module (32).

2. The marine source tracing system for nuclear pollutants according to claim 1, characterized in that: The service backend module (21) collects, organizes and temporarily stores the data based on the obtained complete data, which facilitates the reuse of the data and is also a key step to speed up the data processing response, laying a solid foundation for data visualization. The product creation module (22) realizes the front-end drawing for display visualization.

3. A marine source tracing system for nuclear pollutants according to claim 1, characterized in that: The Python language unit (211) is based on the Python language. The data analysis and processing unit (212) fully utilizes the advantages of NumPy, Pandas and SciPy data analysis and processing libraries to design a fast data processing and storage analysis module. Based on the existing pattern data and observation data, the relevant data is classified and processed. The format conversion unit (213) needs to perform a unified standard format conversion on the existing observation data and pattern data for subsequent use and display on the platform because the existing data are inconsistent from different sources and the standards of all sources are not the same. The classification and organization unit (214) classifies and organizes the data to realize the data storage operation.

4. A marine source tracing system for nuclear pollutants according to claim 1, characterized in that: The data analysis and processing unit (212) includes a NumPy database (2121), a Pandas database (2122), and a SciPy database (2123). The NumPy database (2121) is designed to quickly process data into the NumPy database analysis module, and classifies the relevant data according to the existing pattern data and observation data. The Pandas database (2122) is designed to quickly process data into the Pandas database analysis module, and classifies the relevant data according to the existing pattern data and observation data. The SciPy database (2123) is designed to quickly process data into the SciPy database analysis module, and classifies the relevant data according to the existing pattern data and observation data.

5. A marine source tracing system for nuclear pollutants according to claim 1, characterized in that: The product creation module (22) includes a canvas unit (221), a parameter setting unit (222), and a data extraction unit (223). The canvas unit (221) is built on canvas technology and uses canvas calculation to realize front-end drawing for visualization. The parameter setting unit (222) sets parameters so that the front end of the visualization service platform will send a request to the back-end data processing system of the service platform. The data extraction unit (223) extracts data from specified elements in a specified area, at a specified time, and at a specified level, and performs rapid visualization drawing and display on the front end of the service platform.

6. A marine source tracing system for nuclear pollutants according to claim 5, characterized in that: The data extraction unit (223) includes a specified area extraction block (2231), a specified time extraction block (2232), and a specified level extraction block (2233). The specified area extraction block (2231) extracts data from a specified area and performs rapid visualization drawing and display on the front end of the service platform. The specified time extraction block (2232) extracts data from specified elements at a specified time and performs rapid visualization drawing and display on the front end of the service platform. The specified level extraction block (2233) extracts data from specified elements at a specified level and performs rapid visualization drawing and display on the front end of the service platform.

7. A marine source tracing system for nuclear pollutants according to claim 1, characterized in that: The visualization expression module (31) includes contour lines, color-filled maps, profiles and time series, which meet the needs of global 0-168 hour atmospheric nuclear pollutant diffusion products, 0-120 hour marine nuclear pollution diffusion products, diffusion trajectories, diffusion concentrations, and cumulative sedimentation of land and sea areas. The interface display module (32) displays information related to the marine source tracing of pollutants.

8. A marine source tracing system for nuclear contaminants according to claim 1, characterized in that: The visualization module (31) includes contour lines (311), color-filled plots (312), profiles (313), and time series units (314). The contour lines (311) express the marine source of pollutants through contour lines, the color-filled plots (312) express the marine source of pollutants through color-filled plots, the profiles (313) express the marine source of pollutants through profiles, and the time series units (314) express the marine source of pollutants through time series.

9. A marine source tracing system for nuclear pollutants according to claim 1, characterized in that: The sub-platform (4) includes a user management module (41), a parameter setting module (42), and a file management module (43). The user management module (41) manages users of the traceability system body (1), the parameter setting module (42) sets relevant parameters of the traceability system body (1), and the file management module (43) manages files within the traceability system body (1).

10. A marine source tracing system for nuclear pollutants according to claim 1, characterized in that: The information flow platform (5) includes an external support module (51), a data collection module (52), a model system module (53), a data input module (54), and a source tracing output module (55). The external support module (51) relies on the marine operational numerical forecasting system. The data collection module (52) collects historical typical hydrological and meteorological observation data, atmospheric and marine nuclear material observation data, historical marine and atmospheric numerical simulation data, and marine and atmospheric numerical forecasting data. The model system module (53) is divided into a radioactive material model and a marine radioactive material transport model. The data input module (54) inputs accident-related data, and the source tracing output module (55) outputs source tracing-related data.

11. A marine source tracing system for nuclear pollutants according to claim 1, characterized in that: The software configuration platform (6) includes a data preprocessing module (61), a marine nuclear source tracing module (62), and a historical nuclear information query module (63). The data preprocessing module (61) preprocesses the values ​​input to the source tracing system body (1). The marine nuclear source tracing module (62) can trace the source of nuclear pollution in reverse and has a visual operation function. It can input the accident point and the total amount of nuclear leakage to complete the overall forecast. The historical nuclear information query module (63) queries the historical information of nuclear pollution.

12. A marine source tracing system for nuclear pollutants according to claim 1, characterized in that: The interface display module (32) includes an event name unit (321), a location information unit (322), an observation time unit (323), a source tracing time unit (324), a model calculation unit (325), a source tracing trajectory unit (326), a particle count unit (327), and a real-time monitoring unit (328). The event name unit (321) names the nuclear leak event. The location information unit (322) displays the latitude and longitude of the nuclear leak. The observation time unit (323) displays the observed time. The source tracing time unit (324) displays the source tracing time length. The model calculation unit (325) performs model calculations based on the data. The source tracing trajectory unit (326) traces the nuclear contamination trajectory. The particle count unit (327) displays the number of particles generated by the nuclear contamination. The real-time monitoring unit (328) monitors the nuclear contamination process in real time.

13. A method for tracing the source of nuclear pollutants in the ocean according to claim 1, characterized in that, Includes the following steps: Step 1: Data Input: Input past forecast data from the Atmospheric and Oceanic Environmental Numerical Prediction System, acquired nuclear pollutant data, and cluster analysis data of backward trajectories based on the Atmospheric and Oceanic Particle Model. Step 2: Formula Input: Input the particle motion formulas for different scenarios. Step 3: Model Construction: Build a marine nuclear pollutant source tracing model. The model can, based on the initial location and time of the first detected nuclear pollutant, deploy backward-tracing particles at the initial location, acquire past Atmospheric and Oceanic Numerical Prediction Data, begin backward source tracing, and, based on the known locations of nuclear facilities, estimate the location of nuclear contamination accidents. Step 4: Model Activation Formula: By inputting the locations of monitored nuclear pollutants Cesium-137, Strontium-90, and Iodine-131, and the time of initial monitoring, and using the forecast results of wind field, flow field, temperature, salinity, and density from the accessed global atmospheric and oceanic numerical forecasting system, the entire atmospheric and oceanic nuclear pollutant source tracing subsystem is started; Step 5, Location Determination: The generated source tracing path dataset is imported into the product creation, integration, and operationalization subsystem to complete the location of the nuclear facility where the nuclear pollutant leak occurred; Step 6, Accident Simulation: The product further conducts simulations of nuclear pollution leak accidents; Step 7, Marine Nuclear Source Tracing and Treatment: Source tracing and treatment of marine nuclear pollutants is carried out.

14. The marine source tracing system and method for nuclear pollutants according to claim 1, characterized in that: In step two, the motion formula specifically states that the particle's motion is controlled by the following equation: The formula can be solved using Euler integrals or Runge-Kutta integrals. For the particle position, The random motion velocity caused by turbulence, Let be the velocity of the drifting particle. The velocity of the horizontally moving particle is . ， ， ， These represent the three components of wind speed. These data are output in real time by the forecasting system. The random motion caused by turbulent diffusion is usually calculated using the "random walk" technique, and its velocity can be expressed as: ， The horizontal or vertical diffusion coefficient is given. The horizontal diffusion coefficient can be calculated using the Smagorinsky formula based on the wind field and seawater velocity.

15. A marine source tracing system and method for nuclear pollutants according to claim 1, characterized in that: The specific process of source tracing in step seven is as follows: Access the webpage: http: / / 192.168.5.60:8000 / , create a new kernel source tracing event on the front end and input the relevant parameters, access the Linux server: 192.168.5.60; access the directory: / home / hks / HKS / NuclearNM / model, open the file OcnBwdCaselists.json, and see the corresponding parameters in the form of a Python dictionary; The front-end submits the "Model Calculation" button for marine nuclear source tracing. To check the system monitoring, based on the system monitoring progress, view the corresponding data results in the background. Navigate to the directory: / home / hks / data / DATA_NuclearNM / ocndata to view the system preprocessing results. Navigate to the directory: / home / hks / data / DATA_NuclearNM / model_result / ocn / CasesBWD / qingdao / output to view the model-generated data 20230201_all.dat. Navigate to the directory: / home / hks / data / DATA_NuclearNM / model_result / ocn / CasesBWD / qingdao / output to view the system post-processing result data 20230201_end_sta.dat.

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