A method and system for pollutant dispersion simulation suitable for complex terrain

Abstract

The application relates to a pollutant diffusion simulation method and system suitable for complex terrains, which comprises the following steps: S1, generating a complex terrain region calculation grid according to satellite image elevation data, wherein the complex terrain region comprises a calculation domain; S2, constructing and dynamically adjusting meteorological data coupling boundary conditions for the side boundary surface and the top surface of the calculation domain; and S3, performing calculation based on a Reynolds time average equation model driving software to generate flow field data of a pollutant diffusion process of the calculation domain. The application provides a high-resolution terrain grid generation method, which restores the real geographical environment features of the complex terrain to the maximum extent, realizes rapid generation of a space grid, guarantees the rationality of calculation input, and further improves the accuracy of numerical simulation of pollutant gas diffusion in the complex terrain.

Description

Technical Field

[0001] This application relates to the field of pollutant diffusion simulation technology, and in particular to a pollutant diffusion simulation method and system suitable for complex terrain. Background Technology

[0002] In scenarios such as chemical accidents, energy extraction, and industrial emissions, the leakage of toxic and harmful gases or particulate matter, coupled with complex terrain and meteorological conditions, makes its diffusion path and concentration distribution difficult to predict, potentially triggering regional environmental pollution incidents and even endangering life and property. Accurately simulating the diffusion process after a pollutant leak and analyzing the interaction mechanisms of topographic dynamics, atmospheric turbulence, and material transport is crucial for improving emergency response capabilities and optimizing risk prevention strategies, and is also an important research direction in environmental science. Real geographical features have a significant and complex impact on pollutant diffusion. Topographical undulations alter airflow through dynamic and thermal effects, thus affecting pollutant transport and diffusion. Dynamically, topography can lead to airflow around, lifting, and enhanced turbulence, making pollutant diffusion paths complex and variable. For example, vortices easily form on the leeward slopes of mountains, exacerbating pollutant concentration fluctuations. Thermodynamically, valley wind circulation and inversion layers alter the vertical diffusion of pollutants, and nighttime inversion layers may cause pollutants to accumulate near the ground. Current pollutant diffusion simulations suffer from insufficient computational accuracy in complex terrain areas and computational errors between simulations and actual results.

[0003] In view of the above, this application is hereby submitted. Summary of the Invention

[0004] This application protects a pollutant diffusion simulation method and system applicable to complex terrain, in order to solve the technical problems of insufficient calculation accuracy in complex terrain areas and calculation errors between simulation and actual results in the prior art.

[0005] The invention protects a method for simulating pollutant diffusion in complex terrain, comprising the following steps: S1, generating a computational grid for a complex terrain region based on satellite image elevation data, wherein the complex terrain region includes a computational domain; S2, constructing and dynamically adjusting meteorological data coupling boundary conditions for the side and top surfaces of the computational domain; and S3, performing calculations based on the Reynolds time-averaged equation model-driven software to generate flow field data of the pollutant diffusion process in the computational domain.

[0006] Furthermore, the step of generating a computational grid for complex terrain regions based on satellite image elevation data includes acquiring satellite digital elevation data and constructing a geometric model of the complex terrain region; constructing a geometric model of non-terrain structures within the computational domain; loading the geometric model of the complex terrain region and the geometric model of non-terrain structures to generate a computational grid for the complex terrain region.

[0007] Further, the step of acquiring satellite digital elevation data and constructing a complex terrain region geometric model comprises: based on a satellite remote sensing data platform, filtering and acquiring satellite digital elevation data according to the longitude and latitude range and accuracy requirement of the simulated region; preprocessing the satellite digital elevation data, which comprises: converting the satellite digital elevation data into a target projection coordinate system, performing data splicing and abnormal value correction, and generating preprocessed satellite digital elevation data; importing the preprocessed satellite digital elevation data, and constructing a continuous three-dimensional complex terrain geometric surface based on discrete points of the satellite digital elevation data to form a complex terrain region geometric model.

[0008] Further, the step of constructing a non-terrain structure geometric model in the calculation domain comprises: acquiring measured data of non-terrain structures in the calculation domain, wherein the non-terrain structure types include buildings, factory areas, and obstacles; and constructing a structure model according to the measured data of the non-terrain structures.

[0009] Further, the step of loading the complex terrain region geometric model and the non-terrain structure geometric model to generate a complex terrain region calculation grid comprises: loading the complex terrain region geometric model and the non-terrain structure geometric model to determine the calculation domain range; acquiring grid generation control parameters to determine the global grid size and the local encryption strategy; identifying pollutant marker points to determine the encryption region and the local grid encryption rule; dividing the geometric model to generate a complex terrain region calculation grid; detecting the complex terrain region calculation grid, and when the detection result does not meet the preset condition, optimizing and adjusting the encryption parameters, and when the detection result meets the preset condition, outputting the complex terrain region calculation grid.

[0010] Further, the step of constructing and dynamically adjusting the meteorological data coupled boundary condition for the side boundary surface and the top surface of the calculation domain comprises: collecting and processing meteorological information data of the calculation domain, wherein the meteorological information data includes wind field information data; fitting a wind speed profile according to the wind field information data to construct a boundary condition set containing terrain-meteorological coupling, wherein the wind speed profile equation is wherein, U is the wind speed at a height Z . U r is the average wind speed at a reference height Z r . α is a wind shear coefficient; and dynamically adjusting the wind shear coefficient in real time for the side boundary surface and the top surface of the calculation domain to correspondingly construct the boundary condition.

[0011] Further, the fitting of the wind speed profile comprises: determining interval time points, and acquiring wind speed data at different height layers at the interval time points; substituting the wind speed data into the wind speed profile equation to solve the U rand the wind shear coefficient, specifically taking the logarithm of the wind speed profile equation: , , converted into a linear fitting , the coefficient b and α are calculated by the least square method U r , the wind speed profile fitting is completed.

[0012] Further, it further comprises a modified wind speed profile model, and the modification of the wind speed profile model comprises: modifying the wind speed profile model based on the combination of the terrain feature gradient parameter, the roughness parameter and the wind speed profile parameter; the correction of the terrain gradient to the reference speed is , U r,corr is the modified reference speed, θ is the terrain gradient, k 1 is the terrain gradient correction coefficient, sign θ is the gradient sign function, positive for uphill and negative for downhill; the correction of the roughness to the wind shear coefficient is , α corr is the modified wind shear coefficient, z 0 is the underlying surface roughness length, k 2 is the terrain roughness correction coefficient, z 0,ref is the reference roughness length.

[0013] Further, the step is calculated based on the Reynolds time average equation model driving software to generate the flow field data of the pollutant diffusion process of the calculation domain, which comprises setting the Reynolds time average equation model solver parameters and the turbulence model based on the boundary conditions; the driving software is used to perform numerical solution on the calculation domain; after the calculation converges, post-processing is performed to obtain the pollutant diffusion flow field data.

[0014] The application also protects a pollutant diffusion simulation system suitable for complex terrain, which applies the method of any one of the above solutions.

[0015] The application has the beneficial effects of improving the calculation accuracy of complex terrain areas, reducing the calculation error between simulation and actual results, restoring the real geographical environment characteristics of complex terrain, and realizing the rapid generation of spatial grids. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the accompanying drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without any creative effort.

[0017] Figure 1 Flow chart for an embodiment of the present application as a whole;

[0018] Figure 2 Reference diagram for a complex terrain area geometric model constructed by satellite data in a mountainous area in an embodiment of the present application;

[0019] Figure 3 Three-dimensional space grid diagram of a chemical plant in a certain mountainous area in an embodiment of the present application;

[0020] Figure 4 Flow chart for outputting a complex terrain area calculation grid in an embodiment of the present application;

[0021] Figure 5 Schematic diagram of a set of monitoring data fitting speed wind speed profiles of a monitoring station in an embodiment of the present application;

[0022] Figure 6 Schematic diagram of a natural gas leakage amount change curve of a certain plant in an embodiment of the present application; DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort are within the scope of protection of the present application.

[0024] The terms used in the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "an" and "the" used in the present application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein means and includes any or all possible combinations of one or more associated listed items.

[0025] The application specifically protects a pollutant diffusion simulation method suitable for complex terrain. The complex terrain condition can refer to a region with significant spatial heterogeneity in surface morphology, such as mountains (slope ≥ 15°), valleys (width < 500 m), plateaus, hills, etc. The terrain undulation and roughness change will significantly affect the airflow movement and pollutant diffusion path. The pollutant can be a toxic and harmful gas or particle.

[0026] In an embodiment of the application, referring to Figure 1 the steps include: S1, generating a complex terrain region calculation grid according to satellite image elevation data, the complex terrain region including a calculation domain; S2, constructing and dynamically adjusting meteorological data coupling boundary conditions for the side boundary surface and the top surface of the calculation domain; S3, performing calculation based on a Reynolds time-averaged equation model driving software to generate flow field data of the pollutant diffusion process in the calculation domain.

[0027] With the above scheme, the elevation data refers to data obtained through a digital elevation model (DEM). The digital elevation model specifically realizes digital simulation of the ground terrain through limited terrain elevation data, that is, digital expression of the terrain surface morphology. The application scheme automatically generates a three-dimensional space calculation grid based on real terrain elevation data, which maximally restores the characteristics of real complex terrain.

[0028] In another embodiment of the application, step S1, generating a complex terrain region calculation grid according to satellite image elevation data, includes: obtaining satellite digital elevation data, constructing a complex terrain region geometric model; constructing a non-terrain structure geometric model within the calculation domain; loading the complex terrain region geometric model and the non-terrain structure geometric model to generate a complex terrain region calculation grid. With the above scheme, the terrain geometric model and the non-terrain structure geometric model are constructed separately, which can more clearly restore the actual regional terrain and structure distribution.

[0029] In another embodiment of the application, the step of obtaining satellite digital elevation data and constructing a complex terrain region geometric model includes: based on a satellite remote sensing data platform, filtering and obtaining satellite digital elevation data according to the latitude and longitude range and accuracy requirements of the simulation region; preprocessing the satellite digital elevation data, which includes converting the satellite digital elevation data to a target projection coordinate system, performing data splicing and outlier correction, and generating preprocessed satellite digital elevation data; importing the preprocessed satellite digital elevation data, constructing a continuous three-dimensional complex terrain geometric surface based on satellite digital elevation data discrete points, and forming a complex terrain region geometric model.

[0030] With the above scheme, the satellite remote sensing data platform can adopt SRTM data service (Shuttle Radar Topography Mission), and can use geographic information system software to perform coordinate system unification on the downloaded satellite digital elevation data, convert the satellite digital elevation data into a target projection coordinate system, perform data splicing, and correct abnormal values. The target projection coordinate system can be a UTM projection (Universal Transverse Mercator).

[0031] In another embodiment of the present application, the preprocessed digital elevation data is imported into a three-dimensional modeling software, such as AutoCAD software, and a continuous three-dimensional complex terrain geometric surface is constructed based on the discrete points of the elevation data by using an interpolation algorithm, so as to form a basic geometric model containing terrain undulation features.

[0032] In another embodiment of the present application, the step of constructing a non-terrain structure geometric model in the calculation domain includes obtaining measured data of non-terrain structures in the calculation domain, and the types of the non-terrain structures include buildings, factory areas, and obstacles; and the step of constructing a building model based on the measured data of the non-terrain structures can further include, when the obtained measured data of the building is building measured data, searching and determining building enhancement construction structure data based on a flow simulation influence factor, and constructing a building model combined with the building enhancement construction structure data; when the obtained measured data of the building is factory area measured data, identifying a factory area construction structure type and marking a pollutant discharge source, and constructing a factory area model; and when the obtained measured data of the building is obstacle measured data, constructing an obstacle model and determining a shielding range of the obstacle to air flow. A complex terrain region geometric model constructed based on satellite data of a certain mountainous area is shown in FIG. 1, and a three-dimensional space grid of a chemical plant in the certain mountainous area is shown in FIG. 2. Figure 2 Figure 3

[0033] ​​By further distinguishing the non-terrain structures into buildings, factory areas, and obstacles and constructing models respectively, the simulation of the diffusion of the pollutants can be more realistic and closer to the actual situation. For the classified construction of the building, the chemical plant area, and the obstacle model in the calculation domain, the three-dimensional entity model is created according to the collected plane data, and the building enhancement construction structure can be used for the local structure such as the door and window and the ventilation port which has a greater impact on the flow simulation. The production device, the factory building, and the wall structure type in the chemical plant area can be identified, the corresponding cylindrical, spherical, cuboid, and irregular surface body model can be constructed according to the design size, and the pollutant emission source position is marked. The diffusion process of the pollutants can be more accurately simulated by marking the pollutant emission source. For the obstacle such as the tree, the telegraph pole, and the soil pile, the cylindrical, conical, or irregular block model can be simplified, the spatial distribution and the geometric parameter are recorded, and the shielding range of the airflow is determined, so that the actual diffusion process of the pollutants can be more accurately simulated.

[0034] In another embodiment of the present application, referring to FIG. 1, the step of loading the complex terrain area geometric model and the non-terrain structure geometric model and generating the complex terrain area calculation grid comprises the following steps. Figure 4 In another embodiment of the present application, referring to FIG. 1, the step of loading the complex terrain area geometric model and the non-terrain structure geometric model and generating the complex terrain area calculation grid comprises the following steps.

[0035] By using the above scheme, the terrain, the artificial structure, and the like geometric model can be loaded in the CFD (Computational Fluid Dynamics) pre-processing software at the same time, the calculation domain range is demarcated, and the diffusion influence range of the pollutants is expanded by 2-5 times. The spatial distribution of the physical quantity can be more finely depicted by encryption, and the calculation accuracy is improved. The initial grid basic size can be set according to the simulation accuracy requirement and the calculation resource. The pollutant marking point is the position or the area which has a greater impact on the diffusion of the pollutants, such as the terrain mutation zone, the building surrounding, and the vicinity of the emission source, and the encryption area and the local grid encryption rule are determined. The software grid generation function can be started to automatically subdivide the geometric model to generate the spatial grid. After the generation, the grid quality detection information is output to check the orthogonality, the length-width ratio, the twist degree, and the like index of the grid. The encryption parameter is adjusted or manually optimized for the unqualified grid area until the CFD simulation calculation requirement is met, and finally the three-dimensional calculation grid model which can be used for the simulation of the diffusion of the pollutants is output.

[0036] In another embodiment of the present application, the models of various structures are introduced into the same coordinate system, and are spatially superimposed with the geometric model of the complex terrain area to check whether there are conflicts such as overlaps and gaps between the models, and the relative positions are calibrated through moving, scaling, cutting and other operations to ensure that the geometric model is consistent with the actual scene in terms of spatial relationship.

[0037] In another embodiment of the present application, the step S2, the step of constructing and dynamically adjusting the meteorological data coupled boundary condition for the side boundary surface and the top surface of the calculation domain comprises: collecting and processing meteorological information data of the calculation domain, wherein the meteorological information data comprises wind field information data; fitting a wind speed profile according to the wind field information data to construct a boundary condition set comprising terrain-meteorological coupling, and the wind speed profile equation is wherein, U is the wind speed at the height Z , U r is the average wind speed at the reference height Z r , α is a wind shear coefficient; and the wind shear coefficient is dynamically adjusted in real time for the side boundary surface and the top surface of the calculation domain to correspondingly construct the boundary condition.

[0038] By using the above scheme, the meteorological information data is collected through meteorological monitoring stations, wind measurement towers and numerical weather prediction to collect data such as wind speed, wind direction, air temperature, air pressure and temperature within the calculation domain, and meteorological data matched with the pollution diffusion period is selected as the focus; the data processing can be a statistical filtering method and a spatial interpolation method to correct abnormal values and missing values in the data.

[0039] In another embodiment of the present application, fitting the wind speed profile comprises: determining interval time, and obtaining wind speed data at different height layers at the interval time; substituting the wind speed data into the wind speed profile equation to solve the U r and the wind shear coefficient, specifically, taking the logarithm of the wind speed profile equation:

[0040] , , which is converted into linear fitting , the coefficients b and a are calculated by the least square method, and then the wind speed profile is obtained. U r

[0041] By using the above scheme, the fitting can be a hourly fitting process, for each day, the measured wind speed data at different height layers at the interval time is selected, the wind speed data is substituted into the wind speed profile equation, and for a certain time, the observation height is Z 1 , Z 2 , …, Z ​n corresponding wind speed is U 1 , U 2 , …, U n。 The above scheme is repeated to complete the wind speed profile fitting of all time points every day, and a per-hour wind speed profile model parameter set is formed. The above scheme can make the wind speed profile fitting more accurate.

[0042] In another embodiment of the application, the wind speed profile model is also corrected, and the correction of the wind speed profile model includes: correcting the wind speed profile model based on the combination of the terrain feature gradient parameter, the roughness parameter and the wind speed profile parameter; the correction of the terrain gradient to the reference speed is , U r,corr is the corrected reference speed, θ is the terrain gradient, k 1 is the terrain gradient correction coefficient, sign θ is the gradient sign function, positive for uphill and negative for downhill; the correction of the roughness to the wind shear coefficient is , α corr is the corrected wind shear coefficient, z 0 is the underlying surface roughness length, k 2 is the terrain roughness correction coefficient, z 0,ref is the reference roughness length.

[0043] Using the above scheme, the average wind speed U r , the wind shear coefficient a at the reference height can be dynamically adjusted in real time according to the corrected wind speed profile set for the side boundary surface and the top surface of the calculation domain, and the boundary conditions are set. The fitting of the speed wind speed profile set of the daily monitoring data of the monitoring station on a certain day is shown in Figure 5 , wherein the horizontal axis represents the speed, and the vertical axis represents the time and height. The speed wind speed profile boundary conditions constructed by considering the terrain roughness and various meteorological field elements in the application are more in line with the actual situation, which ensures the rationality of the calculation input and further improves the accuracy of the numerical simulation of the diffusion of pollutant gases in complex terrain.

[0044] In another embodiment of the application, step S3 includes: driving the software based on the Reynolds time average equation model to perform calculation to generate flow field data of the pollutant diffusion process of the calculation domain, including setting the Reynolds time average equation model solver parameters and the turbulence model based on the boundary conditions; driving the software to perform numerical solution on the calculation domain; and after the calculation converges, performing post-processing to obtain the pollutant diffusion flow field data.

[0045] The above scheme binds the topographic-meteorological coupled boundary conditions to the Reynolds time-averaged equations (continuity and momentum) and component transport equations, ensuring that the inlet / outlet conditions drive the governing equations. The Reynolds time-averaged equations (continuity and momentum equations) and component transport equations are discretized using the second-order finite volume method. The convection term uses the Roe scheme, the diffusion term uses the central difference scheme, and the time term uses the LUSGS implicit scheme. A turbulence model is selected based on the topographic complexity, and the built-in empirical coefficients can be adjusted according to the influence of topographic parameters to adapt to special terrains. The Roe scheme is a classic approximate Riemann solver, while in computational fluid dynamics (CFD), the LUSGS implicit scheme (Lower-Upper Symmetric Gauss-Seidel) is an efficient implicit time-progression algorithm.

[0046] Initiate the numerical solution iterative process for the computational domain, monitor the residual output in real time, until the computation converges.

[0047] After the calculation is completed, the flow field distribution after the pollutants are diffused is obtained. Monitoring points are set up at the pollution source, personnel area and topographic high point to extract wind speed and pollutant concentration parameters in real time, and monitor the peak value of pollutant concentration and diffusion range.

[0048] Simulation results of natural gas leak diffusion process in a certain factory area Figure 6 As shown, Figure 6 The curve showing the change in natural gas leakage over time during the diffusion process is displayed, where the horizontal axis represents time and the vertical axis represents leakage amount.

[0049] This application also protects a pollutant diffusion simulation system suitable for complex terrain, employing the method described in any of the above-mentioned schemes. The numerical simulation method and system for pollutant gas diffusion under complex terrain conditions proposed in this application, based on satellite image elevation data, can parameterize and automatically generate spatial grids for complex terrain. Furthermore, by fitting wind speed profiles based on measured data from meteorological monitoring stations, boundary conditions can be dynamically adjusted according to actual meteorological conditions, ensuring both stable solution and computational accuracy and efficiency of the flow field, significantly improving the ability to simulate pollutant gas diffusion. Through a high-resolution terrain grid generation method, automatic generation technology based on a full-basin grid, and adaptive grid refinement technology, the true geographical environmental characteristics of complex terrain are restored, achieving rapid generation of spatial grids.

Claims

1. A method for simulating diffusion of pollutants suitable for complex terrain, characterized by, The method comprises the steps of: S1, generating a complex terrain area calculation grid according to satellite image elevation data, the complex terrain area comprising a calculation domain; S2, constructing and dynamically adjusting meteorological data coupled boundary conditions for the side boundary surface and the top surface of the calculation domain; S3, performing calculation based on a Reynolds time-averaged equation model driving software to generate flow field data of the calculation domain pollutant diffusion process; Step S1 comprises constructing a non-terrain structure geometric model in the calculation domain; the step of constructing a non-terrain structure geometric model in the calculation domain comprises obtaining non-terrain structure measured data in the calculation domain, the non-terrain structure types including factory area, building, and obstacle, and constructing a structure model according to the non-terrain structure measured data; the step of constructing a structure model according to the non-terrain structure measured data comprises, when the obtained structure measured data is building measured data, searching and determining building enhanced construction structure data based on a flow simulation influence factor, and constructing a building model combined with the building enhanced construction structure data; when the obtained structure measured data is a factory area, identifying a factory area construction structure type and marking a pollutant discharge source, and constructing a factory area model; when the obtained structure measured data is an obstacle, constructing an obstacle model and determining a range of air flow shielding by the obstacle; Step S2 comprises collecting and processing meteorological information data of the calculation domain, the meteorological information data comprising wind field information data; fitting a wind speed profile according to the wind field information data to construct a boundary condition set containing terrain-meteorological coupling; and further comprising correcting a wind speed profile model, the corrected wind speed profile model comprising a wind speed profile model corrected based on a combination of a terrain feature slope parameter, a roughness parameter, and a wind speed profile parameter.

2. The pollutant dispersion simulation method for complex terrain according to claim 1, characterized by, The step of generating a complex terrain area calculation grid according to satellite image elevation data comprises: obtaining satellite digital elevation data and constructing a complex terrain area geometric model; loading the complex terrain area geometric model and the non-terrain structure geometric model to generate a complex terrain area calculation grid.

3. The pollutant dispersion simulation method for complex terrain according to claim 2, characterized by, The step of obtaining satellite digital elevation data and constructing a complex terrain area geometric model comprises: filtering and obtaining satellite digital elevation data based on a satellite remote sensing data platform according to the latitude and longitude range and accuracy requirements of the simulation area; preprocessing the satellite digital elevation data, the preprocessing comprising coordinate system unification and conversion to a target projection coordinate system, data splicing, and abnormal value correction on the satellite digital elevation data to generate preprocessed satellite digital elevation data; importing the preprocessed satellite digital elevation data, constructing a continuous three-dimensional complex terrain geometric surface based on satellite digital elevation data discrete points, and forming a complex terrain area geometric model.

4. The method for pollutant dispersion simulation applicable to complex terrain according to any one of claims 2-3, characterized in that, The step of loading the complex terrain area geometric model and the non-terrain structure geometric model to generate a complex terrain area calculation grid comprises: loading the complex terrain area geometric model and the non-terrain structure geometric model to determine the calculation domain range; obtaining grid generation control parameters to determine global grid size and local encryption strategy; identifying pollutant marker points to determine encryption areas and local grid encryption rules; The sectioned geometric model generates a complex terrain area calculation grid, detects the complex terrain area calculation grid, optimizes and adjusts the encryption parameters when the detection result does not satisfy the preset condition, and outputs the complex terrain area calculation grid when the detection result satisfies the preset condition.

5. The pollutant dispersion simulation method for complex terrain according to claim 1, wherein, The step of constructing and dynamically adjusting the meteorological data coupling boundary condition for the side boundary surface and the top surface of the calculation domain comprises: The wind speed profile equation is wherein, U is the height Z of the wind speed at the height U r is the reference height Z r of the average wind speed, and a is the wind shear coefficient; the wind shear coefficient is dynamically adjusted in real time for the side boundary surface and the top surface of the calculation domain, and the boundary conditions are correspondingly constructed.

6. The pollutant dispersion simulation method for complex terrain according to claim 5, wherein, The step of fitting the wind speed profile comprises: Determine the interval time, and obtain the wind speed data of different height layers at the interval time; Substitute the wind speed data into the wind speed profile equation to solve the U r and the wind shear coefficient, specifically taking the logarithm of the wind speed profile equation: , into a linear fit , calculate the coefficients b and a by least squares, to obtain U r , complete the wind speed profile fitting.

7. The pollutant dispersion simulation method for complex terrain according to claim 6, wherein, The corrected wind speed profile model comprises: The terrain slope correction to the reference velocity is , is the corrected reference velocity, θ is the terrain slope, k 1 is the terrain slope correction coefficient, is the slope sign function, positive for uphill, negative for downhill; The roughness correction to the wind shear coefficient is , α corr is the corrected wind shear coefficient, z 0 is the underlying surface roughness length, k 2 is the terrain roughness correction coefficient, z 0,ref is the reference roughness length.

8. The pollutant dispersion simulation method for complex terrain according to claim 1, wherein, The step of calculating based on the Reynolds time average equation model driving software to generate the flow field data of the pollutant diffusion process of the calculation domain comprises: Based on the boundary condition, set the Reynolds time average equation model solver parameters and the turbulence model; The driving software performs numerical solution on the calculation domain; after the calculation converges, post-processing is performed to obtain the pollutant diffusion flow field data.

9. A pollutant dispersion simulation system suitable for complex terrain, characterized by, The method of any one of claims 1-8 is applied.

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