Rapid modeling method and system for complex mountain terrain wind field characteristic research
By combining Blender and GIS with Python scripts to parse meteorological data, a complex mountain wind field analysis model was established. This solved the problems of inaccurate wind field simulation and high computational cost in existing technologies, and enabled efficient and accurate research on wind field characteristics.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-29
- Publication Date
- 2026-04-07
AI Technical Summary
Existing technologies struggle to accurately simulate the wind field characteristics of complex mountainous environments, leading to improper optimization of photovoltaic array layouts, low land utilization, and high computational costs.
Blender software was used to accurately locate the target construction site and model the 3D terrain. Elevation and terrain data were obtained by combining GIS. Meteorological monitoring data was analyzed using Python scripts to establish a wind field analysis model with the terrain grid surface as the base. Reasonable grid division was determined through grid sensitivity analysis.
It improves the accuracy and computational efficiency of wind field simulation, reduces human error, rationally allocates computational resources, lowers computational costs, and improves land utilization.
Smart Images
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Abstract
Description
Technical Field
[0001] This invention belongs to the field of wind field characteristic research technology, and relates to a rapid modeling method and system for wind field characteristic research in complex mountainous terrain. Background Technology
[0002] As a populous country, my country's per capita land resources are less than one-third of the world average, with arable land accounting for only 12.5% of its total land area. Furthermore, with accelerating urbanization, available land resources are becoming increasingly scarce. However, my country's topography exhibits significant diversity, with mountains, hills, and plateaus accounting for approximately 69% of the total land area. These regions are ecologically fragile, difficult to develop, and have long faced the dual pressures of low land use efficiency and ecological protection. Promoting the extension of the photovoltaic industry to these complex terrain areas has become an important path to balance efficient use of land space with large-scale development of clean energy. Statistics show that the unused mountainous area suitable for photovoltaic construction in the Yunnan-Guizhou-Sichuan region alone exceeds 50,000 square kilometers. If rationally developed, this could provide over 100 billion kilowatt-hours of clean electricity annually, reducing carbon emissions by hundreds of millions of tons.
[0003] However, the wind field characteristics of complex mountain environments differ fundamentally from those of isolated mountains or flat terrain. Influenced by dramatic topographic relief, numerous gullies, and micro-landforms (such as steep slopes, ridges, and canyons), the near-surface layer (0... The wind field at a height of 200 meters exhibits high spatial heterogeneity and temporal dynamics. Specifically: 1) The vertical wind shear rate varies non-linearly with slope and aspect; leeward slopes are prone to forming backflow vortices, while windward slopes experience local acceleration due to topographic lifting; 2) Wind speeds surge in mountain gaps and canyons due to the "tunneling effect," while closed basins form weak wind zones due to airflow obstruction; 3) Microscopic differences in surface roughness (such as vegetation cover and exposed rock) further exacerbate the spatial differentiation of turbulence intensity and wind angle of attack. These non-uniform wind field characteristics pose significant challenges to the structural safety of photovoltaic array supports, module heat dissipation efficiency, and the accuracy of power generation prediction—a wind load assessment deviation exceeding 10% could increase the risk of support overturning by more than 30%, while local wind speed prediction errors directly affect inverter heat dissipation design, causing module temperatures to rise by 5%. 10℃, which in turn leads to an 8% decrease in power generation efficiency. 15%.
[0004] Traditional mesoscale meteorological models, while capable of simulating regional-scale wind fields, typically have a grid resolution greater than 1 kilometer, making it difficult to resolve wind field distortions caused by abrupt topographic changes ranging from hundreds to tens of meters. Microscale models based on computational fluid dynamics, although capable of improving accuracy through localized grid refinement, suffer from exponentially increasing computational costs and often simplify the surface as a smooth slope or homogeneous rough elements, ignoring the geometric heterogeneity of real terrain. Furthermore, existing methods heavily rely on meteorological station observation data to construct initial boundary conditions, but meteorological stations are sparse in complex mountainous environments, resulting in limited spatial representativeness of observational data and further complicating model calibration. This not only threatens engineering safety but also leads to improper optimization of photovoltaic array layout, resulting in a 10% reduction in land utilization. 20%. Summary of the Invention
[0005] To address the shortcomings of existing technologies, this invention aims to provide a rapid modeling method and system for studying wind field characteristics in complex mountainous terrain.
[0006] To achieve the above objectives, the present invention adopts the following technical solution: This invention provides a rapid modeling method for studying wind field characteristics in complex mountainous terrain, comprising the following steps: acquiring elevation and topographic data of the target construction site based on a GIS platform, locating the target construction site in Blender 3D space through coordinate registration, determining the terrain truncation boundary to generate a corresponding 3D terrain model, and exporting it as an STL terrain file; parsing meteorological monitoring data based on a Python script, extracting the geographic coordinate information of the monitoring points, matching the geographic coordinate information with the spatial coordinate system in the STL terrain file, and extracting the spatial coordinate information of the points to be analyzed in the STL terrain file; establishing a wind field analysis model with the terrain grid surface as the base based on the spatial coordinate information; performing grid sensitivity analysis on the wind field analysis model to determine the grid division.
[0007] Furthermore, the step of acquiring elevation and terrain data of the target construction site based on the GIS platform, locating the target construction site in Blender 3D space through coordinate registration, determining the terrain truncation boundary to generate the corresponding 3D terrain model, and exporting it as an STL terrain file includes: locating the target construction site in Blender, determining the scope of the target construction site and the terrain data of the target construction site; and locating the boundary longitude of the target construction site in the GIS platform. , and latitude , Convert the elevation terrain data to elevation terrain data; input the elevation terrain data into Blender to form a terrain model, and cut the terrain model according to the number of cuts; use the displacement modifier and subdivision surface modifier in the modifier panel of Blender to convert the elevation terrain data into an STL terrain file.
[0008] Furthermore, based on the parsing of meteorological monitoring data using Python scripts, the geographic coordinate information of the monitoring points is extracted. This geographic coordinate information is then matched with the spatial coordinate system in the STL terrain file to extract the spatial coordinate information of the points to be analyzed in the STL terrain file. This includes: using a Python program to convert the latitude and longitude coordinates of the target construction site into the center of a circle in a plane coordinate system; converting the latitude and longitude coordinates of the boundary points of the target construction site into plane distances and angles relative to the center of the circle; calculating the plane coordinates of the boundary points based on the plane distances and angles; and determining a rectangular area with the center of the circle as its centroid based on the plane coordinates.
[0009] Furthermore, the step of establishing a wind field analysis model with the terrain mesh surface as the base includes: opening the STL terrain file and generating a terrain mesh surface; establishing a cylindrical model for wind field simulation; and cutting the terrain mesh surface and the cylindrical model to obtain a wind field analysis model with the terrain surface as the ground.
[0010] Furthermore, the wind field analysis model is divided into 8 parts according to wind direction for calculation and analysis under multi-wind-direction conditions.
[0011] Furthermore, a grid sensitivity analysis is performed on the wind field analysis model to determine the grid division, which includes: dividing the wind field model into a near-ground region and a far-ground region along the vertical height; using a first grid for the near-ground region and a second grid for the far-ground region; and determining the grid division based on the division results of the first and second grids through sensitivity analysis.
[0012] Furthermore, the near-ground region is 10 to 100 meters above the ground, and the far-ground region is more than 100 meters above the ground.
[0013] Furthermore, the first grid has a resolution of 0.1 meters to 5 meters, and the second grid has a resolution of 5 meters to 50 meters; the ratio of the resolution of the first grid to the resolution of the second grid is 1:5 to 1:20.
[0014] Furthermore, the transition area between the first and second grids is connected using a progressive grid densification method.
[0015] This invention also provides a rapid modeling system for studying wind field characteristics in complex mountainous terrain, comprising: an acquisition module: locating the target construction site and determining the cutoff boundary using Blender, acquiring elevation and terrain data corresponding to the target construction site through GIS, and importing the elevation and terrain data into Blender software and saving it as an STL terrain file; an extraction module: using Python to parse meteorological monitoring data and extract the spatial coordinate information of the required analysis points from the STL terrain file; a model building module: using the spatial coordinate information to build a wind field analysis model with the terrain grid surface as the base in CFD software; and an analysis module: performing grid sensitivity analysis on the wind field analysis model and determining the grid division.
[0016] Compared with the prior art, the present invention has the following beneficial technical effects: This invention presents a rapid modeling method for studying wind field characteristics in complex mountainous terrain. It uses Blender software to precisely locate the target construction site and determine the cutoff boundary, which is not only intuitive and efficient but also significantly improves the accuracy and efficiency of preliminary preparation work. Combining GIS technology to acquire elevation and topographic data ensures the accuracy and real-time nature of topographic information, laying a solid foundation for subsequent analysis. Seamlessly importing the elevation and topographic data acquired from GIS into Blender and saving it as an STL topographic file simplifies the conversion process between different software and maintains data consistency and integrity. Using Python scripts to parse meteorological monitoring data and automatically extract the spatial coordinate information of the required analysis points from the STL topographic file greatly improves the automation of data processing, reduces the error rate of manual operation, and accelerates the speed of data analysis. Establishing a wind field analysis model with the topographic grid surface as the base in CFD software ensures a high degree of fit between the model and the actual terrain, improving the accuracy and reliability of wind field simulation. By performing grid sensitivity analysis on the wind field analysis model, a scientific and reasonable grid division scheme can be determined, ensuring both computational accuracy and effective control of computational costs.
[0017] This invention provides a rapid modeling method for studying wind field characteristics in complex mountainous terrain. The transition region between the first and second grids is connected by progressively denser grids, which gradually changes the grid density within the transition region. A denser grid is used in critical areas, while a sparser grid is maintained in non-critical areas. This progressively denser grid connection can effectively reduce the amount of computation and improve computational efficiency while ensuring computational accuracy, allowing for a more reasonable allocation of computational resources and avoiding unnecessary computational waste.
[0018] This invention presents a rapid modeling method for studying wind field characteristics in complex mountainous terrain. By using a high-resolution first grid for the near-surface region and dynamically adjusting the grid resolution based on terrain undulation gradients and wind speed variation gradients, it can more accurately capture complex flow details within the surface boundary layer. This helps to more accurately simulate wind field behavior near the ground, including changes in wind speed, direction, and turbulence characteristics, thereby improving the overall simulation accuracy. For the far-surface region, a coarser-resolution second grid is used, with the resolution gradually decreasing with increasing altitude. This significantly reduces computational load and optimizes the utilization of computational resources while maintaining a certain level of simulation accuracy. This grid partitioning strategy allows computational resources to be more rationally allocated to key areas, improving computational efficiency. Attached Figure Description
[0019] Figure 1 This is a flowchart of a rapid modeling method for studying wind field characteristics in complex mountainous terrain, as described in this invention. Figure 2 This is a schematic diagram illustrating the location and numbering of the target construction site in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure for cutting the terrain model in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure for generating a terrain mesh surface based on an STL terrain file in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of a wind field analysis model established using a terrain grid surface as the base in an embodiment of the present invention; Figure 6 This is a schematic diagram of the wind field model division in an embodiment of the present invention; Figure 7 for Figure 6 Sensitivity analysis results under wind zone segmentation. Detailed Implementation
[0020] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of 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 skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0021] Example 1 This invention provides a rapid modeling method for studying wind field characteristics in complex mountainous terrain, such as... Figure 1The process includes locating the target construction site and determining the cutoff boundary using Blender; acquiring elevation and terrain data corresponding to the target construction site using GIS; importing the elevation and terrain data into Blender and saving it as an STL terrain file; parsing meteorological monitoring data using Python to extract the spatial coordinate information of the points to be analyzed from the STL terrain file; establishing a wind field analysis model with the terrain grid surface as the base in CFD software based on the spatial coordinate information; and performing grid sensitivity analysis on the wind field analysis model to determine the grid division.
[0022] Specifically, Blender is a 3D modeling software used for modeling complex surfaces such as organic organisms or terrain.
[0023] First, determine the target construction site and the terrain data to import. Create a new project in Blender and import the GIS data of the target area using a built-in plugin or a third-party tool (such as BlenderGIS). Taking a construction site in a mountainous area as an example, first load the Shapefile boundary data and DEM elevation data in QGIS. Use QGIS's "Export Grid Layer" function to convert the terrain to .obj format, ensuring the coordinate system is set to WGS84 (EPSG:4326). Then, in Blender, load the converted terrain file via File→Import→Wavefront(.obj) and use a georeferencing tool to align the coordinate system. For higher precision, a GeoTIFF elevation map can be overlaid, and the grayscale elevation can be mapped to 3D terrain using the shader editor to accurately locate the target area. , Longitude and [ , Latitude, such as Figure 2 As shown.
[0024] Secondly, obtain elevation and topographic data from GIS. In QGIS, select the latitude and longitude boundaries of the target construction site, and use the raster extraction → mask clipping tool to extract local elevation data from the global DEM elevation data. To balance accuracy and computational efficiency, select a DEM with a resolution of 5m. When exporting, use the "CSV grid point" format (containing X / Y / Z coordinates) or directly generate STL format using the 3D Print Toolbox. If exporting as CSV, the point cloud data needs to be converted into a mesh surface in Blender using a Python script or plugin (such as the 3D-Print Toolbox) to ensure that the elevation values are correctly mapped to the Z-axis.
[0025] Next, edit the terrain model and perform cutting operations. In Blender's edit mode, select the terrain model and use the Knife Tool to perform multi-level cuts. For example, if you need to preserve the core construction area, cut along the boundary [ , ]and[ , Draw the cutting line, press K to activate the tool, drag the cutting path, press Enter to confirm, and then delete the redundant parts. Figure 3 As shown. If the terrain is complex, the Loop Cut tool can be used to increase the number of segments, or a Boolean modifier can be used to precisely cut through a cube reference object to finally obtain a clean terrain model that fits the construction plan.
[0026] After editing, switch to object mode and add a Displace Modifier and a Subdivision Surface Modifier to the terrain. The Displace Modifier requires the original DEM grayscale image as texture input; set the intensity parameter to enhance terrain undulation details. For the Subdivision Surface Modifier, select the "Catmull-Clark" algorithm and set the subdivision level to 2 to smooth the model surface. Finally, export the model via File→Export→STL, check the "Apply Modifiers" option, set the unit to meters, and ensure the model size matches the actual site. This will generate an STL terrain file that can be directly used for 3D printing or engineering simulation.
[0027] Use a Python program to convert the latitude and longitude coordinates of the target construction site into the center of a circle in a plane coordinate system; convert the latitude and longitude coordinates of the boundary points of the target construction site into plane distances and angles relative to the center of the circle; calculate the plane coordinates of the boundary points based on the plane distances and angles; and determine the rectangular range with the center of the circle as its centroid based on the plane coordinates.
[0028] Specifically, a Python script is written to read latitude and longitude data from a CSV (comma-separated value) file or a database. The latitude and longitude are then converted into planar coordinates relative to the center of the construction site, and the results are output.
[0029] Based on spatial coordinate information, a wind field analysis model with a terrain mesh surface as the base is established in CFD software. Specifically, open ANSYS Fluent (a general-purpose computational fluid dynamics software) and enter the Geometry module. Select Spaceclaim (a direct modeling software) and then import the STL format terrain model file. Ensure that the imported model is correct and that its position and scale meet the requirements. In Spaceclaim, select Tool → Auto Skin to generate the terrain mesh surface, as shown below. Figure 4As shown. Determine the mesh resolution to ensure it accurately reflects terrain details without increasing computational complexity. Create a cylindrical model with its base aligned with the curved surface of the terrain mesh. Use Spaceclaim's cutting tools (such as Split Body) to cut the cylinder to the terrain mesh, resulting in a wind field analysis model with the terrain mesh surface as its base. Check that it perfectly matches the terrain. Figure 5 As shown.
[0030] A grid sensitivity analysis is performed on the wind field analysis model to determine the grid division. In this embodiment, the wind field analysis model is a cylinder, divided into 8 parts according to the wind direction, as follows: Figure 6 As shown, when performing calculations and analyses under multiple wind direction conditions by changing the wind direction, it is only necessary to modify the definitions of the inlet and outlet boundary surfaces during preprocessing. Only one mesh generation is required, saving a lot of time and greatly improving computational efficiency.
[0031] Specifically, the wind field model is divided into near-surface and far-surface regions along its vertical height. A first grid is used for the near-surface region, with a resolution that ensures accurate capture of wind speed changes and terrain undulations. The first grid resolution is dynamically adjusted based on the terrain undulation gradient and wind speed change gradient to capture flow details within the surface boundary layer. A second grid is used for the far-surface region, with a coarser resolution than the first grid, and its resolution gradually decreases with increasing height. The second grid is used to reduce computational load and improve efficiency. It should be noted that a progressive mesh densification connection is used in the transition region between the first and second grids. A denser grid is used in critical areas, while a sparser grid is maintained in non-critical areas. This progressive mesh densification connection effectively reduces computational load and improves computational efficiency while maintaining computational accuracy, allowing for a more rational allocation of computational resources and avoiding unnecessary computational waste. The resolution range of the first grid is 0.1 meters to 5 meters, the resolution range of the second grid is 5 meters to 50 meters, and the resolution ratio of the first grid to the second grid is 1:5 to 1:20.
[0032] The near-ground region is 10 to 100 meters above the ground, and the far-ground region is more than 100 meters above the ground.
[0033] Based on the grid division results of the first and second grids, a suitable grid density and type are selected through sensitivity analysis. Flow field simulations are performed on different grid division schemes to check the stability of wind field distribution and calculation results. The results of different grid schemes are compared, and sensitivity analysis is conducted to determine... Figure 7 As shown, the optimal solution is selected to ensure both computational accuracy and efficiency.
[0034] Example 2 This invention provides a rapid modeling system for studying wind field characteristics in complex mountainous terrain, comprising: an acquisition module, an extraction module, a model building module, and an analysis module.
[0035] The module consists of the following components: Acquisition Module: Based on Blender, the target construction site is located and the interception boundary is determined. Elevation and topographic data corresponding to the target construction site are obtained through GIS and imported into Blender software to be saved as an STL topographic file; Extraction Module: Used to parse meteorological monitoring data using Python to extract the spatial coordinate information of the required analysis points from the STL topographic file; Model Building Module: Used to build a wind field analysis model with the topographic grid surface as the base in CFD software based on the spatial coordinate information; Analysis Module: Used to perform grid sensitivity analysis on the wind field analysis model and determine the grid division.
[0036] The rapid modeling system for studying wind field characteristics in complex mountainous terrain provided by this invention can implement the same method steps as the above-mentioned method, so it will not be described again.
[0037] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
Claims
1. A rapid modeling method for studying wind field characteristics in complex mountainous terrain, characterized in that, Includes the following steps: The elevation and topographic data of the target construction site are obtained based on the GIS platform. The target construction site is located in the Blender 3D space through coordinate registration. The terrain truncation boundary is determined to generate the corresponding 3D terrain model and export it as an STL terrain file. Meteorological monitoring data is parsed using Python scripts to extract the geographic coordinate information of monitoring points. The geographic coordinate information is then matched with the spatial coordinate system in the STL terrain file to extract the spatial coordinate information of the points to be analyzed in the STL terrain file. Based on spatial coordinate information, a wind field analysis model with the terrain grid surface as the base is established; A grid sensitivity analysis was performed on the wind field analysis model to determine the grid division.
2. The rapid modeling method for studying wind field characteristics in complex mountainous terrain according to claim 1, characterized in that: The process involves acquiring elevation and topographic data of the target construction site based on a GIS platform, locating the target construction site in Blender 3D space through coordinate registration, determining the terrain truncation boundaries to generate a corresponding 3D terrain model, and exporting it as an STL terrain file, including: Locate the target construction site in Blender, and determine the scope and terrain data of the target construction site. In the GIS platform, the boundary longitude of the target construction site is […]. , and latitude , Convert to elevation topographic data; Elevation and terrain data are input into Blender to form a terrain model, and the terrain model is cut according to the number of cuts. Use the Displacement and Subdivision modifiers in Blender's modifier panel to convert elevation terrain data into an STL terrain file.
3. The rapid modeling method for studying wind field characteristics in complex mountainous terrain according to claim 2, characterized in that, This paper uses Python scripts to parse meteorological monitoring data, extracts the geographic coordinates of monitoring points, matches these geographic coordinates with the spatial coordinate system in an STL terrain file, and extracts the spatial coordinates of the points to be analyzed from the STL terrain file. This includes: Use a Python program to convert the latitude and longitude coordinates of the target construction site into the center of a circle in a plane coordinate system; Convert the latitude and longitude coordinates of the boundary points of the target construction site into planar distances and angles relative to the center of the circle; Calculate the planar coordinates of the boundary points based on the planar distance and angle; The rectangular area with the center of the circle as its centroid is determined based on planar coordinates.
4. The rapid modeling method for studying wind field characteristics in complex mountainous terrain according to claim 1, characterized in that, The establishment of the wind field analysis model with the terrain grid surface as the base includes: Open the STL terrain file and generate a terrain mesh surface; A cylindrical model for wind field simulation is established. The terrain mesh surface and the cylindrical model are then cut to obtain a wind field analysis model with the terrain surface as the ground.
5. The rapid modeling method for studying wind field characteristics in complex mountainous terrain according to claim 4, characterized in that: The wind field analysis model is divided into 8 parts according to wind direction for calculation and analysis under multi-wind-direction conditions.
6. The rapid modeling method for studying wind field characteristics in complex mountainous terrain according to claim 1, characterized in that, A grid sensitivity analysis was performed on the wind field analysis model to determine the grid division, including: The wind field model is divided into near-ground and far-ground regions along the vertical height. A first grid is used for the near-ground region, and a second grid is used for the far-ground region; Based on the division results of the first and second grids, the grid division is determined through sensitivity analysis.
7. The rapid modeling method for studying wind field characteristics in complex mountainous terrain according to claim 6, characterized in that: The near-ground region is 10 to 100 meters above the ground, and the far-ground region is more than 100 meters above the ground.
8. The rapid modeling method for studying wind field characteristics in complex mountainous terrain according to claim 6, characterized in that: The first grid has a grid resolution of 0.1 meters to 5 meters, and the second grid has a grid resolution of 5 meters to 50 meters. The ratio of the resolution of the first grid to the resolution of the second grid is 1:5 to 1:
20.
9. The rapid modeling method for studying wind field characteristics in complex mountainous terrain according to claim 6, characterized in that: The transition area between the first and second grids is connected using a progressive grid densification method.
10. A rapid modeling system for studying wind field characteristics in complex mountainous terrain, characterized in that, include: Acquisition module: Based on Blender, the target construction site is located and the interception boundary is determined. The elevation and terrain data corresponding to the target construction site are obtained through GIS. The elevation and terrain data are imported into Blender software and saved as an STL terrain file. Extraction module: Used to parse meteorological monitoring data using Python and extract the spatial coordinate information of the points to be analyzed in the STL terrain file; Model building module: Used to build a wind field analysis model with the terrain grid surface as the base in CFD software based on spatial coordinate information; Analysis module: Used to perform grid sensitivity analysis on the wind field analysis model and determine the grid division.