Surface contamination simulation detection method, device and system

Abstract

The application discloses a surface pollution simulation detection method, device and system, and relates to the technical field of pollution simulation detection. The method comprises the following steps: constructing a fluid diffusion area three-dimensional space model according to space parameters of a to-be-detected area, and dividing the three-dimensional space model into a fluid domain space body grid and a ground surface boundary layer grid; adding radioactive gas particles, and setting the density and leakage rate of the radioactive gas particles; calculating the deposition velocity of the radioactive gas particles in the fluid domain space body grid and the particle concentration of the radioactive gas particles in the ground surface boundary layer grid according to a computational fluid dynamics method; further calculating the deposition flux and the deposition activity; assigning the deposition activity to NFC tags corresponding to the ground surface boundary layer grid, and detecting the NFC tags to complete surface pollution simulation detection. The embodiment of the application can more accurately predict the diffusion trend and deposition condition of radioactive pollutants, and improves the simulation accuracy.

Description

Technical Field

[0001] This application belongs to the field of pollution simulation and detection technology, and in particular relates to a surface pollution simulation and detection method, device and system. Background Technology

[0002] There is currently no clear calculation model for surface contamination. Empirical data is usually used in the process of collecting surface contamination data, which can lead to inaccurate data, a lack of close integration with real training scenarios, and problems such as misjudgment and misinterpretation. Training for fire protection and other emergency response cannot be based on data with a clear degree of contamination.

[0003] Fluorescence staining can distinguish different forms of radiation and supports fine retesting, but it cannot measure concentration; it is a scalar quantity, and parameters are mainly set in the background, making it impossible to integrate with accident scenarios. It is also difficult to measure in strong light environments, limiting its use. Furthermore, the simulants are consumables, expensive, hindering widespread adoption, and the measurement effectiveness is limited, as simulants generally cannot be retested within tens of minutes. RFID tags, on the other hand, simply input data into the tags, and the scientific validity of the data cannot be verified. It mainly relies on measurement experience, measuring typical empirical values. Neither of these methods can be combined with actual accident scenarios for scenario simulation. Summary of the Invention

[0004] The purpose of this application is to provide a surface contamination simulation detection method, device and system to simulate and detect the diffusion and deposition of radioactive gas particles in a specific area. By constructing a three-dimensional spatial model of the fluid diffusion area and using computational fluid dynamics (CFD) methods for simulation, the simulation detection of surface contamination can be finally achieved.

[0005] To achieve the above objectives, the solution proposed in this application is:

[0006] In a first aspect, embodiments of this application provide a surface contamination simulation detection method, comprising:

[0007] A three-dimensional spatial model of the fluid diffusion region is constructed based on the spatial parameters of the area to be detected. The three-dimensional spatial model of the fluid diffusion region includes the air inlet.

[0008] The three-dimensional spatial model of the fluid diffusion region is meshed into a fluid domain spatial volume mesh and a surface boundary layer mesh.

[0009] Radioactive gas particles are added to the three-dimensional spatial model of the fluid diffusion region, and the parameters of the radioactive gas particles are set, including the density and leakage rate of the radioactive gas particles.

[0010] Based on the density and leakage rate of radioactive gas particles, the deposition rate of radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid are calculated using computational fluid dynamics methods.

[0011] The deposition flux is calculated based on the deposition rate of radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid.

[0012] Depositional activity is calculated based on sedimentation flux and the surface area of ​​the surface boundary layer grid.

[0013] The sedimentation activity is assigned to the NFC tag corresponding to the surface boundary layer grid, and the NFC tag is detected to complete the surface pollution simulation detection.

[0014] Furthermore, the three-dimensional spatial model of the fluid diffusion region is meshed into a fluid domain spatial volume mesh and a surface boundary layer mesh, including:

[0015] The finite volume method was used to mesh the three-dimensional spatial model of the fluid diffusion region, dividing it into a fluid domain spatial volume mesh and a surface boundary layer mesh.

[0016] Furthermore, based on the density and leakage rate of radioactive gas particles, and using computational fluid dynamics methods, the deposition rate of radioactive gas particles in the fluid domain space grid and the particle concentration in the surface boundary layer grid are calculated, including:

[0017] The concentration diffusion equation for radioactive gas particles is constructed as shown below:

[0018]

[0019] Among them, C i Indicates particle concentration; u represents air velocity; D i ε represents the molecular diffusion rate of radioactive gas particles i; p The eddy diffusivity of turbulent flow; v s，i This represents the settling velocity of radioactive gas particles i.

[0020] eddy diffusivity ε of turbulence p Depends on friction speed u * The distance y from the wall is given by the following formula:

[0021] ε p ∝u * y

[0022]

[0023]

[0024] Among them, Tw ρ represents the wall shear stress, ρ represents the air density, and y represents the wall distance, which is the distance between the closest grid layer of the surface boundary layer and the ground.

[0025] The equation for the conservation of air phase mass / momentum is constructed as follows:

[0026]

[0027] Where u represents the air velocity vector; Represents the air velocity component; Indicates the diffusion coefficient; Represents the source term of the equation;

[0028] when At that time, the air phase mass / momentum conservation equation is the air phase mass conservation equation.

[0029] Furthermore, by simultaneously solving the concentration diffusion equation and the air phase mass / momentum conservation equation, a system of simultaneous equations is obtained. Based on computational fluid dynamics methods and the density and leakage rate of radioactive gas particles, the system of simultaneous equations is solved to obtain the particle concentration C of radioactive gas particles in the surface boundary layer grid. i .

[0030] Furthermore, based on the density and leakage rate of radioactive gas particles, and using computational fluid dynamics methods, the deposition rate of radioactive gas particles in the fluid domain space grid and the particle concentration in the surface boundary layer grid are calculated, including:

[0031] The deposition rate of radioactive gas particles in a fluid domain space grid is calculated using the following formula:

[0032]

[0033] Among them, v d，j Indicates deposition rate; C i Indicates particle concentration; u represents air velocity; D i ε represents the molecular diffusion rate of radioactive gas particles i; p The eddy diffusivity of turbulent flow; v S，i This represents the settling velocity of radioactive gas particles i.

[0034] Furthermore, the deposition flux is calculated based on the deposition rate of radioactive gas particles in the fluid domain space grid and the particle concentration in the surface boundary layer grid, as shown in the following formula:

[0035] J d，i =v d,i ·C b，i

[0036] Among them, J d，i Indicates deposition flux; v d，i This represents the deposition rate of radioactive gas particles in a fluid domain space volume grid; C b，i This indicates the particle concentration of radioactive gas particles in the Earth's surface boundary layer grid.

[0037] Furthermore, sedimentary activity is calculated based on sedimentary flux and the surface area of ​​the surface boundary layer grid, as shown in the following formula:

[0038] Where Ap,i represents sedimentation activity; Jd,t,p,i represents the sedimentation flux of the i-th grid within time step t; a p，i This represents the surface area of ​​the Earth's boundary layer grid.

[0039] Secondly, embodiments of this application provide a surface contamination simulation detection device, comprising:

[0040] The model building module is configured to construct a three-dimensional spatial model of the fluid diffusion region based on the spatial parameters of the region to be detected. The three-dimensional spatial model of the fluid diffusion region includes the air inlet.

[0041] The mesh generation module is configured to perform mesh generation on the three-dimensional spatial model of the fluid diffusion region, dividing it into a fluid domain spatial volume mesh and a surface boundary layer mesh.

[0042] The parameter setting module is configured to add radioactive gas particles to the three-dimensional spatial model of the fluid diffusion region and set the parameters of the radioactive gas particles, including the density and leakage rate of the radioactive gas particles.

[0043] The first calculation module is configured to calculate the deposition rate of radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid based on the density and leakage rate of the radioactive gas particles, using computational fluid dynamics methods.

[0044] The second calculation module is configured to calculate the deposition flux based on the deposition rate of radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid.

[0045] The third calculation module is configured to calculate sedimentary activity based on sedimentary flux and the surface area of ​​the surface boundary layer grid.

[0046] The simulation detection module is configured to assign sediment activity values ​​to the NFC tags corresponding to the surface boundary layer grid and detect the NFC tags to complete the surface contamination simulation detection.

[0047] Thirdly, embodiments of this application provide a surface contamination simulation detection system, the system including a processor and a memory, the memory storing a computer program, the computer program being loaded and executed by the processor to implement the surface contamination simulation detection method as provided in the first aspect of embodiments of this application.

[0048] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, is used to implement the surface contamination simulation detection method as described in the first aspect of embodiments of this application.

[0049] The surface contamination simulation detection method provided in this application has the following advantages compared with the prior art:

[0050] This application embodiment constructs a three-dimensional spatial model of the fluid diffusion region and divides it into grids to accurately simulate the diffusion and deposition process of radioactive gas particles in the fluid domain spatial volume grid and the surface boundary layer grid. This accuracy helps to more accurately predict the diffusion trend and deposition of radioactive pollutants, providing a reliable basis for subsequent pollution control and risk assessment.

[0051] This application employs computational fluid dynamics (CFD) methods, combining the concentration diffusion equation of radioactive gas particles with the mass / momentum conservation equation of the air phase, to efficiently calculate the deposition rate and particle concentration of particles in the fluid domain and the surface boundary layer. This calculation method not only improves the accuracy of the simulation but also greatly shortens the calculation time, which helps to achieve real-time and dynamic pollution simulation.

[0052] This application embodiment comprehensively assesses the deposition of radioactive gas particles in the area to be detected by calculating deposition flux and deposition activity. This information is of great value for formulating pollution control measures, optimizing emergency plans, and assessing pollution risks. At the same time, the deposition activity is assigned to an NFC tag and detected, enabling real-time recording and traceability of pollution information, providing strong support for subsequent pollution monitoring and management. Attached Figure Description

[0053] Figure 1 A schematic flowchart of the surface contamination simulation detection method according to an embodiment of this application is shown;

[0054] Figure 2 A structural block diagram of a surface contamination simulation detection device according to an embodiment of this application is shown;

[0055] Figure 3 A structural block diagram of a computer device according to an embodiment of this application is shown. Detailed Implementation

[0056] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, it should be noted that, for ease of description, only the parts relevant to this application are shown in the accompanying drawings, not the entire structure. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application.

[0057] The terms “comprising” and “having”, and any variations thereof, used in this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0058] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0059] like Figure 1 As shown in the figure, this application provides a surface contamination simulation detection method, including the following steps:

[0060] Step 101: Construct a three-dimensional spatial model of the fluid diffusion region based on the spatial parameters of the area to be detected. The three-dimensional spatial model of the fluid diffusion region includes the air inlet.

[0061] Step 101 is the starting step of this application embodiment, which involves constructing a three-dimensional spatial model of the fluid diffusion region based on the spatial parameters of the region to be detected, and this model needs to include the air inlet.

[0062] Specifically, a three-dimensional spatial model of the fluid diffusion region is constructed based on the spatial parameters of the region to be detected. These parameters include, but are not limited to, the size, shape, height, obstacle distribution, and ventilation conditions of the region. These parameters form the basis for constructing the three-dimensional spatial model, determining its accuracy and practicality.

[0063] The three-dimensional spatial model of the fluid diffusion region is a digital 3D model used to simulate the diffusion of radioactive gas particles within the area to be detected. This model needs to accurately reflect the spatial characteristics of the area to be detected in order to perform precise simulation calculations.

[0064] In the three-dimensional spatial model of the fluid diffusion region, the air inlet is a crucial component. It simulates the entry point for air into the area to be detected and is one of the key factors to consider during the simulation. The design of the air inlet needs to be based on the actual ventilation conditions. For example, the size, location, and number of air inlets all need to be designed according to the specific circumstances.

[0065] This application embodiment collects spatial parameters of the area to be detected, including information such as the area's size, shape, height, and obstacle distribution. This information can be obtained through on-site measurement, drawing review, etc. Based on the complexity of the area to be detected and the simulation requirements, a suitable 3D modeling tool is selected for modeling. For example, CAD (Computer-Aided Design) software, GIS (Geographic Information System) software, Fluent, OpenFoam, or dedicated fluid simulation software can be used for modeling.

[0066] In the modeling tool, a three-dimensional spatial model of the fluid diffusion area is gradually constructed based on the collected spatial parameters, including steps such as drawing the area's boundaries, adding obstacles, and setting air inlets. After completing the initial modeling, the model needs to be verified and adjusted. This is done through comparison with the actual area and simulation tests to ensure that the model accurately reflects the spatial characteristics and ventilation conditions of the area to be tested.

[0067] In summary, step 101 is the foundation of the entire surface contamination simulation and detection method. An accurate and detailed three-dimensional spatial model can provide a reliable basis for subsequent simulation calculations, thereby ensuring the accuracy and practicality of the simulation results and providing a solid foundation for subsequent simulation calculations.

[0068] Step 102: Mesh the three-dimensional spatial model of the fluid diffusion region into a fluid domain spatial volume mesh and a surface boundary layer mesh.

[0069] The purpose of step 102 is to divide the three-dimensional spatial model of the fluid diffusion region into a fluid domain spatial volume grid and a surface boundary layer grid. This step is also the basis for subsequent simulation calculations. The rationality and accuracy of the grid division directly affect the accuracy and reliability of the simulation results.

[0070] In this embodiment, the Finite Volume Method (FVM) is used for mesh generation. The FVM is particularly suitable for simulating complex physical fields such as fluid dynamics. Using the FVM, the fluid diffusion region is divided into multiple fluid domain spatial volume meshes via FluentMeshing. These meshes are the basic units for subsequent simulation calculations, used to describe the motion and distribution of the fluid in three-dimensional space. Based on the fluid domain spatial volume meshes, a surface boundary layer mesh is further generated. The surface boundary layer is an important region where fluids interact with solid surfaces, and its internal flow characteristics are typically complex. By generating a surface boundary layer mesh, the flow and deposition processes of fluids near the surface can be simulated more accurately.

[0071] After mesh generation, a mesh quality check is required. This check includes assessing mesh continuity, orthogonality, and aspect ratio to ensure the mesh meets the requirements of the simulation. Finally, the generated mesh is output in a specific file format (such as CGNS or FLUENT) for subsequent computational fluid dynamics (CFD) software simulations.

[0072] In summary, step 102 is a crucial step in meshing the three-dimensional spatial model of the fluid diffusion region. Its implementation includes selecting a meshing method, determining the mesh type and size, dividing the fluid domain spatial volume mesh and the surface boundary layer mesh, mesh quality checking, and mesh output. A reasonable mesh generation provides an accurate foundation for subsequent simulation calculations.

[0073] Step 103: Add radioactive gas particles to the three-dimensional spatial model of the fluid diffusion region and set the parameters of the radioactive gas particles, including the density and leakage rate of the radioactive gas particles.

[0074] Step 103 involves adding radioactive gas particles to the three-dimensional spatial model of the fluid diffusion region and setting the parameters of these particles. Specifically, these parameters include the density and leakage rate of the radioactive gas particles.

[0075] The density of radioactive gas particles refers to the mass of particles per unit volume. This parameter is crucial for simulating the diffusion and deposition behavior of particles in fluids. The magnitude of the density directly affects the motion of particles in the fluid, including their settling velocity and diffusion range. Therefore, when setting this parameter, the physical characteristics of radioactive gas particles in the actual environment must be fully considered.

[0076] Leakage rate refers to the quantity or mass of radioactive gas particles leaking out per unit time. This parameter determines the speed and quantity of particles entering the fluid diffusion zone, thus affecting the distribution and deposition of particles in the model. The leakage rate setting needs to be adjusted according to the actual leakage situation or simulation requirements to ensure the accuracy and reliability of the simulation results.

[0077] Step 103 is one of the foundations of the entire simulation detection method. Only by correctly setting the parameters of radioactive gas particles can the diffusion and deposition behavior of particles in the fluid be accurately simulated, thereby calculating key indicators such as deposition flux and deposition activity. These indicators are of great significance for assessing the degree of surface contamination and formulating pollution control measures.

[0078] In summary, step 103 plays a crucial role in the surface contamination simulation and detection method. Correctly setting the parameters for radioactive gas particles is one of the key steps to ensure the accuracy and reliability of the simulation results.

[0079] Step 104: Based on the density and leakage rate of the radioactive gas particles, calculate the deposition rate of the radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid using computational fluid dynamics methods.

[0080] Step 104 is a core component of the surface contamination simulation and detection method, involving the calculation of the deposition rate of radioactive gas particles in the fluid domain spatial volume grid and the particle concentration in the surface boundary layer grid using the density and leakage rate of these particles. This step relies on computational fluid dynamics (CFD) methods to accurately simulate and calculate the diffusion and deposition processes of particles.

[0081] This application first constructs a concentration diffusion equation for radioactive gas particles, as shown in the following formula:

[0082]

[0083] Among them, C i Indicates particle concentration; u represents air velocity; D i ε represents the molecular diffusion rate of radioactive gas particles i; p The eddy diffusivity of turbulent flow; v s，i This represents the settling velocity of radioactive gas particles i.

[0084] The concentration-diffusion equation describes the change in the concentration distribution of radioactive gas particles in the air over time. The variables in the equation include particle concentration, air velocity, molecular diffusivity of the radioactive gas particles, turbulent eddy diffusion rate, and settling velocity of the radioactive gas particles. The turbulent eddy diffusion rate is related to friction velocity and wall distance, which further influences the diffusion behavior of the particles.

[0085] eddy diffusivity ε of turbulence p Depends on friction speed u * The distance y from the wall is given by the following formula:

[0086] ε p ∝u * y

[0087]

[0088] Among them, T w ρ represents the wall shear stress, ρ represents the air density, and y represents the wall distance, which is the distance between the nearest grid cell in the surface boundary layer and the ground.

[0089] After constructing the concentration diffusion equation for radioactive gas particles, this application embodiment constructs an air phase mass / momentum conservation equation to describe the mass and momentum conservation of airflow, as shown in the following formula:

[0090]

[0091] Where u represents the air velocity vector; Represents the air velocity component; Indicates the diffusion coefficient; Represents the source term of the equation;

[0092] when At that time, the air phase mass / momentum conservation equation is the air phase mass conservation equation.

[0093] The concentration diffusion equation and the air phase mass / momentum conservation equation are combined to form a system of equations. This system of equations is solved using computational fluid dynamics methods and the density and leakage rate of radioactive gas particles. The solution provides information on the particle concentration of radioactive gas particles in the surface boundary layer grid.

[0094] This application embodiment calculates the deposition rate of radioactive gas particles in a fluid domain spatial volume grid, using the following formula:

[0095]

[0096] Among them, v d，j Indicates deposition rate; C iIndicates particle concentration; u represents air velocity; D i ε represents the molecular diffusion rate of radioactive gas particles i; p The eddy diffusivity of turbulent flow; v s，i This represents the settling velocity of radioactive gas particles i.

[0097] This formula takes into account multiple factors such as particle concentration, air velocity, molecular diffusion rate of radioactive gas particles, eddy diffusion rate of turbulence, and settling velocity of radioactive gas particles.

[0098] In summary, step 104 is a crucial step in the surface contamination simulation and detection method, involving complex mathematical and physical calculations. By constructing and solving the concentration diffusion equation, the air phase mass / momentum conservation equation, and calculating the deposition rate, the deposition rate of radioactive gas particles in the fluid domain spatial volume grid and the particle concentration in the surface boundary layer grid can be accurately simulated and calculated.

[0099] Step 105: Calculate the deposition flux based on the deposition rate of radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid.

[0100] In this embodiment, step 105 involves calculating the deposition flux based on the deposition rate of radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid. This step is crucial for assessing the deposition of radioactive contaminants, predicting their potential environmental impacts, and developing appropriate protective measures.

[0101] Deposition flux refers to the mass or activity of radioactive gas particles deposited per unit area per unit time. In step 105, the deposition flux can be calculated by combining the deposition rate of radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid, as shown in the following formula:

[0102] J d，i =v d，i ·C b，i

[0103] Among them, J d，i Indicates deposition flux; v d，i This represents the deposition rate of radioactive gas particles in a fluid domain space volume grid; C b，i This indicates the particle concentration of radioactive gas particles in the Earth's surface boundary layer grid.

[0104] Deposition rate is a physical quantity that describes how quickly particulate matter is deposited onto a solid surface in a fluid. It is influenced by a variety of factors, including the physical properties of the particulate matter (such as density, shape, and size), the properties of the fluid (such as flow rate, temperature, and viscosity), and the properties of the solid surface (such as roughness and material). In step 105, accurate deposition rate data is crucial for calculating the deposition flux.

[0105] Particle concentration refers to the number of radioactive gas particles per unit volume. In a surface boundary layer grid, the distribution of particle concentration reflects the deposition of radioactive pollutants on the surface. By measuring or calculating particle concentration, we can understand the diffusion and deposition patterns of radioactive pollutants in the environment, and thus assess their impact on the environment and human health.

[0106] The calculation results of sedimentation flux are of great significance for the formulation of environmental protection policies and measures. For example, in areas surrounding nuclear facilities, monitoring sedimentation flux can help detect the spread of radioactive contaminants in a timely manner, enabling appropriate protective measures to be taken to protect the environment and public health. Furthermore, sedimentation flux data can be used to assess the long-term environmental impacts of nuclear accidents or leaks, providing a scientific basis for post-disaster recovery and reconstruction.

[0107] In summary, step 105, by accurately calculating the deposition flux, provides a better understanding of the deposition of radioactive gas particles.

[0108] Step 106: Calculate sedimentary activity based on sedimentary flux and the surface area of ​​the surface boundary layer grid.

[0109] In this embodiment, step 106 involves calculating sedimentary activity based on sedimentary flux and the surface area of ​​the surface boundary layer grid. This step is important for assessing the degree of surface contamination, determining the distribution of pollution sources, and developing effective pollution control measures.

[0110] Depositional activity refers to the total radioactivity intensity of radioactive material deposited per unit area. In surface contamination simulation detection methods, depositional activity can be obtained by calculating the deposition flux (i.e., the mass or quantity of radioactive material passing through a unit area per unit time) and the surface area of ​​the surface boundary layer grid, as shown in the following formula:

[0111] Among them, A p，i Indicates sedimentary activity; J d，t，p，i a represents the deposition flux of the i-th grid within time step t; p，i This represents the surface area of ​​the Earth's boundary layer grid.

[0112] First, based on the calculation results from the previous steps, the deposition flux of each grid needs to be determined. Next, the surface area of ​​each surface boundary layer grid needs to be determined, which can be obtained directly during the meshing of the 3D spatial model in step 102, or through subsequent calculations and processing. Finally, the total deposition activity is obtained by adding the ratio of the deposition flux of each grid to its surface area.

[0113] The calculation results in step 106 are crucial for assessing the degree of surface contamination. By comparing the deposition activity in different areas, the distribution and diffusion of pollution sources can be determined. Furthermore, the calculation results of deposition activity can be used to develop effective pollution control measures, such as setting up isolation zones and improving ventilation.

[0114] In practical applications, step 106 is often combined with other steps to form a complete surface contamination simulation and detection system. This system can monitor and assess the diffusion and deposition of radioactive materials in the environment in real time, providing strong support for environmental protection and nuclear safety.

[0115] In summary, step 106 involves the calculation of deposition activity, which is of great significance for assessing the degree of surface contamination, determining the distribution of pollution sources, and formulating pollution control measures.

[0116] Step 107: Assign the sedimentation activity value to the NFC tag corresponding to the surface boundary layer grid, and detect the NFC tag to complete the surface contamination simulation detection.

[0117] Step 107 is the final step of the entire detection method, which involves assigning the calculated sediment activity to the NFC tags corresponding to the surface boundary layer grid and detecting these NFC tags to complete the surface contamination simulation detection.

[0118] Specifically, sedimentary activity is assigned to NFC tags corresponding to the surface boundary layer grid, and the NFC tags are then detected to complete the surface contamination simulation detection. NFC (Near Field Communication) tags are a contactless data transmission technology that allows information exchange over short distances. In this detection method, NFC tags are used to store and transmit sedimentary activity information for each surface boundary layer grid.

[0119] After calculating the sedimentary activity of each surface boundary layer grid, this information needs to be accurately recorded and stored on the corresponding NFC tag to ensure accuracy and completeness. Detection of the NFC tag typically involves using an NFC reader to read the information stored on the tag. This process can be automated to improve efficiency and accuracy. The information read by the reader allows for a quick understanding of the contamination status of each grid.

[0120] Once all NFC tags have been correctly read and their deposition activity information analyzed, the surface contamination simulation test can be considered complete. This information can be used to assess the level of contamination, develop protective measures, and conduct subsequent environmental monitoring.

[0121] In practical applications, this surface contamination simulation detection method can be used to assess contamination levels in various scenarios, such as nuclear power plants and chemical plants where radioactive or chemical contamination may exist. By simulating the diffusion and deposition processes of pollutants, the degree of contamination in different areas can be predicted and assessed, allowing for the implementation of appropriate protective measures. Furthermore, this method can also be used in environmental monitoring and pollution early warning systems, enabling timely warnings and responsive measures by monitoring and analyzing the diffusion of pollutants in real time.

[0122] In summary, step 107 is the final step in the entire surface contamination simulation and detection method, and a crucial step in translating the calculation results into practical applications. By accurately recording and reading the deposition activity information on the NFC tag, precise assessment and monitoring of contamination can be achieved.

[0123] like Figure 2 As shown in the figure, this application provides a surface contamination simulation and detection device, including a model building module 201, a mesh generation module 202, a parameter setting module 203, a first calculation module 204, a second calculation module 205, a third calculation module 206, and a simulation and detection module 207, wherein:

[0124] The model building module 201 is configured to build a three-dimensional spatial model of the fluid diffusion region based on the spatial parameters of the region to be detected. The three-dimensional spatial model of the fluid diffusion region includes an air inlet.

[0125] Mesh generation module 202 is configured to perform mesh generation on the three-dimensional spatial model of the fluid diffusion region, dividing it into a fluid domain spatial volume mesh and a surface boundary layer mesh.

[0126] The parameter setting module 203 is configured to add radioactive gas particles to the three-dimensional spatial model of the fluid diffusion region and set the parameters of the radioactive gas particles, including the density and leakage rate of the radioactive gas particles.

[0127] The first calculation module 204 is configured to calculate the deposition rate of radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid based on the density and leakage rate of the radioactive gas particles and by computational fluid dynamics methods.

[0128] The second calculation module 205 is configured to calculate the deposition flux based on the deposition rate of radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid.

[0129] The third calculation module 206 is configured to calculate sedimentary activity based on sedimentary flux and the surface area of ​​the surface boundary layer grid.

[0130] The simulation detection module 207 is configured to assign the deposition activity to the NFC tag corresponding to the surface boundary layer grid and detect the NFC tag to complete the surface contamination simulation detection.

[0131] The surface contamination simulation detection device in this application embodiment can be a computer device or a component within a computer device, such as an integrated circuit or a chip. The computer device can be a terminal or other devices besides a terminal. For example, the computer device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle computer device, mobile internet device (MID), ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc., and can also be a server, network attached storage (NAS), personal computer (PC), etc. This application embodiment does not specifically limit the device.

[0132] The surface contamination simulation detection device provided in this application embodiment can achieve... Figure 1 The various processes implemented in the surface contamination simulation detection method embodiment will not be described again here to avoid repetition.

[0133] This application also provides a computer device, such as... Figure 3 As shown, the computer device includes a processor 301 and a memory 302. The memory 302 stores programs or instructions that can run on the processor 301. When the program or instructions are executed by the processor 301, they implement the various steps of the above-mentioned surface contamination simulation detection method and achieve the same technical effect. To avoid repetition, they will not be described in detail here.

[0134] It should be noted that, in this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0135] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for simulating and detecting surface contamination, characterized in that, The method includes: A three-dimensional spatial model of the fluid diffusion region is constructed based on the spatial parameters of the region to be detected. The three-dimensional spatial model of the fluid diffusion region includes an air inlet. The three-dimensional spatial model of the fluid diffusion region is meshed into a fluid domain spatial volume mesh and a surface boundary layer mesh. Radioactive gas particles are added to the three-dimensional spatial model of the fluid diffusion region, and the parameters of the radioactive gas particles are set, including the density and leakage rate of the radioactive gas particles. Based on the density and leakage rate of the radioactive gas particles, the deposition rate of the radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid are calculated by computational fluid dynamics methods. The deposition flux is calculated based on the deposition rate of the radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid. The sedimentary activity is calculated based on the sedimentation flux and the surface area of ​​the surface boundary layer grid. The deposition activity is assigned to the NFC tag corresponding to the surface boundary layer grid, and the NFC tag is detected to complete the surface pollution simulation detection.

2. The surface contamination simulation detection method as described in claim 1, characterized in that, The process of meshing the three-dimensional spatial model of the fluid diffusion region into a fluid domain spatial volume mesh and a surface boundary layer mesh includes: The finite volume method was used to mesh the three-dimensional spatial model of the fluid diffusion region, dividing it into a fluid domain spatial volume mesh and a surface boundary layer mesh.

3. The surface contamination simulation detection method as described in claim 1, characterized in that, The deposition flux is calculated based on the deposition velocity of the radioactive gas particles in the fluid domain space grid and the particle concentration in the surface boundary layer grid, as shown in the following formula: in, Indicates deposition flux; This indicates the deposition rate of the radioactive gas particles in the fluid domain space volume grid; This indicates the particle concentration of the radioactive gas particles in the surface boundary layer grid.

4. The surface contamination simulation detection method as described in claim 1, characterized in that, The sedimentary activity is calculated based on the sedimentary flux and the surface area of ​​the surface boundary layer grid, using the following formula: in, Indicates sediment activity; Indicates time step Inner Deposition flux of each grid; This represents the surface area of ​​the surface boundary layer grid.

5. A surface contamination simulation detection device, characterized in that, The device includes: The model building module is configured to build a three-dimensional spatial model of the fluid diffusion region based on the spatial parameters of the region to be detected. The three-dimensional spatial model of the fluid diffusion region includes an air inlet. The mesh generation module is configured to perform mesh generation on the three-dimensional spatial model of the fluid diffusion region, dividing it into a fluid domain spatial volume mesh and a surface boundary layer mesh. The parameter setting module is configured to add radioactive gas particles to the three-dimensional spatial model of the fluid diffusion region and set the parameters of the radioactive gas particles, including the density and leakage rate of the radioactive gas particles. The first calculation module is configured to calculate the deposition rate of the radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid based on the density and leakage rate of the radioactive gas particles and by computational fluid dynamics methods. The second calculation module is configured to calculate the deposition flux based on the deposition rate of the radioactive gas particles in the fluid domain space volume grid and the particle concentration in the surface boundary layer grid. The third calculation module is configured to calculate sedimentary activity based on the sedimentation flux and the surface area of ​​the surface boundary layer grid. The simulation detection module is configured to assign the deposition activity to the NFC tag corresponding to the surface boundary layer grid and detect the NFC tag to complete the surface contamination simulation detection.

6. A surface contamination simulation detection system, the system comprising a processor and a memory, wherein the memory stores a computer program, characterized in that, The computer program is loaded and executed by the processor to implement the surface contamination simulation detection method as described in any one of claims 1 to 4.

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