A downscaling numerical simulation method for bridge wind-temperature coupling considering real terrain

Abstract

The present invention provides a downscaling numerical simulation method for wind-temperature coupling of bridges considering real terrain, belonging to the technical field of bridge structure design. It includes: determining the calculation area of the mesoscale model according to the geographical location of the bridge and adopting multi-layer grid nesting to improve the calculation accuracy; obtaining terrain static data and initial meteorological field data and configuring physical schemes; establishing the geometric model of the small-scale model through 3D modeling software; performing fitting block division and extraction point planning according to the morphology of the inlet surface of the small-scale model calculation domain; extracting the inlet wind speed and temperature data through the mesoscale model by using the Cressman interpolation method and fitting by using the least square method to obtain the wind speed and temperature functions of the inlet surface of the small-scale model; loading the geometric model and the wind speed and temperature functions of the inlet surface according to the characteristics of the bridge structure material, establishing the small-scale model by using the CFD method, and solving the environmental wind, temperature field and structural response. The present invention improves the simulation authenticity and reduces the redundancy of the simulation work.

Description

Technical Field

[0001] The present invention provides a downscaled numerical simulation method for wind-temperature coupling of bridges considering real terrain, belonging to the technical field of bridge structure design. Background Art

[0002] With the continuous development of bridge engineering, the design, construction, and maintenance of bridge structures are facing increasingly complex environmental factors. Among them, wind and temperature are the main environmental factors that have an adverse effect on bridges, significantly affecting the safety and durability of bridge structures. In the actual environment, especially in complex terrains such as difficult mountainous areas, there is a complex process of coupling of atmospheric dynamics and thermodynamics. The air pressure will change due to the influence of temperature. Hot air rises and cold air descends, and the air pressure difference leads to the formation of wind. At the same time, the wind affects the temperature, which in turn affects the air pressure. Therefore, the wind-temperature coupling effect in the environment is formed. Moreover, most of the difficult mountainous areas have steep terrain and large topographic undulations, resulting in a significant height difference between adjacent valleys. At the same time, due to the diverse landforms, the distribution characteristics of its wind field and temperature field are extremely complex. For bridge structures, the temperature field in the natural environment mainly undergoes heat transfer with the structure through convective heat transfer and radiative heat transfer (the process of heat exchange between two objects with different temperatures and not in contact through electromagnetic waves). Due to the constraints on the structure, the temperature-induced effect (structural deformation caused by non-uniform temperature difference) is generated, which may cause excessive deformation or even cracking of the structure. The wind field directly acts on the surface of the structure and is extremely susceptible to the influence of the terrain environment, thus affecting the wind field distribution near the structure, and further affecting the convective heat transfer process on the surface of the structure. Therefore, ignoring the real terrain conditions and the wind-temperature coupling effect in the environment may lead to a large deviation between the simulation results and the actual situation, and thus cannot reflect the true response of the structure.

[0003] In order to analyze the response of bridges under the wind-temperature coupling effect in complex environments, it is particularly important to develop a downscaled numerical simulation method for wind-temperature coupling of bridges considering real terrain.

[0004] CN114139263A discloses a numerical simulation method for wind-temperature coupling of bridges considering the local wind field on the bridge deck. By using the theoretical formula of the thermal boundary layer, the height of the thermal boundary layer on the surface of the bridge structure is calculated; by using the wind field model, the wind speed at the height of the thermal boundary layer is solved; by fitting the wind speed data at the bridge entrance and the height of the thermal boundary layer using the least squares method, a reduction coefficient is obtained; the ambient temperature and the bridge thermal radiation value in the bridge site area are obtained; a numerical model for wind-temperature coupling of the bridge is established, and the parameters of the numerical model for wind-temperature coupling of the bridge are fitted; the finite element method is used to solve the temperature field of the bridge structure. This method has the following technical drawbacks:

[0005] (1) High cost and lack of authenticity in temperature acquisition: For the acquisition of environmental temperature, it largely relies on theoretical formulas and requires the measurement of the daily maximum and minimum temperatures. The density of temperature samples is low and cannot reflect the true temperature physical field.

[0006] (2) Unrealistic and inaccurate wind field model: For the simulation of the structural wind field, the influence of real environmental factors (such as the coupling effect between temperature and wind field) and terrain is not considered. The inlet wind profile of the wind field model is unrealistic and cannot reflect the true wind field distribution.

[0007] (3) Insufficient precision in the analysis of the temperature-induced effect of the structure: After obtaining the temperature field of the structure using this technology, it is necessary to extract the temperature load and then load it on the structure. In this process, only a limited number of discrete temperature load boundaries can be extracted, and the extraction points of the load field are not comprehensive enough; the two-way coupling effect between the load field and the structure is not considered, and only the result of the unidirectional action of the temperature load field on the structure can be reflected. Summary of the Invention

[0008] The present invention provides a downscaling numerical simulation method for bridge wind-temperature coupling considering real terrain, and the technical problems to be solved are as follows:

[0009] (1) Obtain real, accurate, and detailed environmental temperature and wind speed: First, use the WRF model to simulate the real mesoscale environmental temperature and wind speed of the required time and area; through the CFD method, establish a small-scale model according to the bridge structure and terrain, where the inlet boundary conditions are obtained by least-squares fitting of the temperature and wind speed results in the mesoscale, and during the fitting process, block fitting is performed according to the terrain trend of the inlet surface to improve the simulation accuracy; the simulation area of the mesoscale model is large enough to make the inlet conditions of the small-scale model more real and reasonable, and then drive the small-scale model to operate and solve, so as to obtain the real environmental wind field and temperature field at any position in the simulation domain. The above process considers real terrain factors and the real environmental wind-temperature coupling process.

[0010] (2) Consider the real-time two-way coupling between the load field and the structure: In the small-scale model, the two-way coupling between the environment and the structure is considered, so that the coupling effect of wind and temperature in the environment and the response of the structure can be considered simultaneously during the calculation, without the need to first calculate the environmental field and then load it on the structure, improving the calculation accuracy and reducing the complexity of the simulation work.

[0011] The specific technical solution is: A downscaling numerical simulation method for bridge wind-temperature coupling considering real terrain, including the following steps:

[0012] (1) Determine the calculation area of the mesoscale model according to the geographical location of the bridge, and use multi-level grid nesting to improve the calculation accuracy.

[0013] The simulation is carried out using a three - layer bidirectional nested grid (d01, d02, d03) scheme. The horizontal resolutions of the grids from the outside to the inside are 9 km, 3 km, and 1 km respectively, that is, the grid spacing of the outermost d01 grid is 9 km. The vertical grid layer of the computational domain is set to 50 layers. The top - layer air pressure in the model is set to 5000 Pa, and the default bottom - layer air pressure in the mesoscale model is 1000 Pa. The vertical grid is encrypted below 1 km, with 14 layers of encrypted grids set, and the height of the bottom - most grid is 25 m;

[0014] The time integration step is set to 1 s, and the Lambert projection scheme is selected for the map projection during the simulation.

[0015] (2) Obtain the topographic static data and the initial meteorological field data, and configure the physical scheme.

[0016] During the WRF model calculation process, two types of initial data need to be input first, namely the topographic static data and the initial meteorological field data. The complete three - dimensional initial data within the computational domain is obtained through the integral and interpolation programs built into the model. The data of the initial meteorological field needs to select the file of the target simulation period and be loaded in the WRF model. The planetary boundary layer scheme uses the YSU scheme, the RRTM long - wave radiation scheme, the Dudhia short - wave radiation scheme, the Goddard micro - physical process scheme, the Betts - Miller - Janjic cumulus convection parameterization scheme, the Monin - Obukhov (modified MM5) surface layer parameterization scheme, and the Noah land surface process scheme. Among them, the cumulus convection scheme is only enabled for the first - layer grid.

[0017] (3) Establish the geometric model of the small - scale model through 3D modeling software.

[0018] The geometric model in the small - scale model is divided into a topographic model and a structural model.

[0019] The establishment process of the topographic model is as follows: Obtain the digital elevation model (DEM, Digital Elevation Model) of the bridge site area, import it into the Globalmapper software for slicing processing to obtain the topographic data information of the small - scale simulation domain. The small - scale model uses the (x, y, z) three - dimensional coordinate form. Before being loaded into the small - scale model, a spatial coordinate transformation is required, as shown in the following formulas (1) - (2). Then, use the 3D modeling software Rhino to establish the topographic surface.

[0020]

[0021] In the formula is the longitude and latitude coordinate in the WGS84 coordinate system, (x, y) is the coordinate in the Mercator projection coordinate system, R is the average radius of the earth, and e is the first eccentricity of the earth ellipsoid.

[0022] The structural model is a solid model established by the 3D modeling software Rhino based on the structural geometric information.

[0023] (4) According to the morphology of the inlet surface of the small-scale model calculation domain, perform fitting block division and extraction point planning.

[0024] When extracting the results of the meso-scale model, first perform fitting block division and extraction point planning according to the terrain trend and the size of the inlet surface area of the small-scale model.

[0025] (5) Through the meso-scale model, use the Cressman interpolation method to extract the inlet wind speed and temperature data, and use the least squares method for fitting to obtain the wind speed and temperature functions of the inlet surface of the small-scale model.

[0026] The calculation formula of the Cressman interpolation method is as follows:

[0027]

[0028] In the formula, w ij is the weight between the interpolation point and the observation point, d ij is the Euclidean distance between the interpolation point and the observation point, D is the jump threshold of the step function, v i represents the interpolation result of the interpolation point, v j represents the observed value of the sample point, and n represents the number of sample points.

[0029] For the extracted data, use the least squares method for function approximation to obtain the fitting function of the inlet surface. The implementation process of the least squares method is as follows:

[0030] Given the data α0(x), α1(x), …, α n (x), it is necessary to find the function in the function class that minimizes the sum of squared errors as shown in Equation (5) The obtained function is the least squares solution of this function class for this set of data.

[0031]

[0032] (6) According to the material properties of the bridge structure, load the geometric model and the wind speed and temperature functions of the inlet surface, use the CFD method to establish a small-scale model, and solve the environmental wind, temperature field and structural response.

[0033] The geometric model is meshed using ANSYS software. The geometric model is imported into ANSYS software, and further processing of the geometric model is carried out in the SpaceClaim module. First, the surface quality of the model is checked and repaired. Then, data coupling interaction is established between the two contact surfaces of the fluid and the solid. Next, the boundary surfaces are grouped, and then the meshing is carried out in the Fluentmeshing module. The entire model uses tetrahedral unstructured meshes. The terrain boundary, the pylon structure, and the nearby fluid domain are meshed more densely. The height of the first layer of mesh on the terrain surface is 0.1 m, and the boundary layer growth rate is 1.1.

[0034] A small-scale model is established using the CFD software Fluent. When setting the inlet boundary conditions, the velocity inlet and the temperature inlet are selected. The initial information is read and set by writing a UDF (User Define Function) program through the fitted wind speed and temperature functions of the inlet surface. The fluid is considered to be fully developed at the outlet, and the north side of the computational model is set as the pressure outlet boundary. The ground surface and the pylon structure surface of the computational model are set as non-slip wall boundaries; the top surface and the east and west side boundary surfaces of the model are set as symmetry boundaries.

[0035] The FSI (Fluid Structure Interaction) definition between the structural wall boundary and the spatial domain is carried out.

[0036] For the calculation, a pressure-based steady-state solver suitable for low-speed incompressible flow is selected. The turbulence model and the turbulence solution scheme select the SST k-ω and the SIMPLEC algorithm. The discretization format selects the second-order upwind format, and the standard wall function is selected.

[0037] The technical effects of the present invention are as follows:

[0038] A mesoscale model is established through the WRF model, considering the real environmental terrain and rich meteorological physical schemes. The real mesoscale environmental temperature and wind speed of the required time and area are obtained. And because the simulation area of the mesoscale model is large enough, the inlet conditions of the small-scale model are more real and reasonable, thereby driving the operation and solution of the small-scale model.

[0039] Through the CFD method, a small-scale model was established based on the actual bridge structure and terrain. The inlet boundary conditions were obtained by fitting the temperature and wind speed results in the meso-scale model using the least squares method. During the fitting process, block fitting was performed according to the terrain trend of the inlet surface, which solved to a certain extent the boundary wind speed distortion problems such as excessively high surface wind speed and missing wind speed values commonly existing in the model inlet setting, and improved the simulation accuracy.

[0040] In the small-scale model, the two-way coupling between the environment and the structure was considered, so that the results of the wind-temperature coupling of the environment and the response of the structure could be obtained simultaneously during the calculation, improving the simulation authenticity and reducing the complexity of the simulation work. Brief Description of the Drawings

[0041] Figure 1 is the flowchart of the method of the present invention;

[0042] Figure 2 is the schematic diagram of the multi-layer nested grid of the simulation area of the present invention;

[0043] Figure 3 is the schematic diagram of the establishment of the overall geometric model of the present invention;

[0044] Figure 4 is the schematic diagram of the block division of the inlet surface and the distribution of data extraction points of the present invention;

[0045] Figure 5 is the schematic diagram of the overall watershed grid of the present invention;

[0046] Figure 6 is the schematic diagram of the surface grid of the present invention;

[0047] Figure 7 is the schematic diagram of the boundary layer grid of the present invention;

[0048] Figure 8 is the schematic diagram of the pylon structure grid of the present invention;

[0049] Figure 9 is the schematic diagram of the solution parameter setting of the present invention. Detailed Embodiments

[0050] The specific technical solution of the present invention will be described in conjunction with the accompanying drawings.

[0051] As Figure 1 shown, a downscaling bridge wind-temperature coupling numerical simulation method considering the actual terrain includes the following steps:

[0052] (1) Determine the calculation area of the meso-scale model according to the geographical location of the bridge, and adopt multi-layer grid nesting to improve the calculation accuracy.

[0053] The mesoscale model is applicable to simulation studies with a resolution of 1 - 10 km. A three-layer two-way nested grid (d01, d02, d03) scheme is adopted for simulation. The horizontal resolutions of the grids from the outside to the inside are 9 km, 3 km, and 1 km respectively, that is, the grid spacing of the outermost d01 grid is 9 km. The number of vertical grid layers in the computational domain is set to 50 layers. The top pressure in the model is set to 5000 Pa, and the default bottom pressure in the mesoscale model is 1000 Pa. Since the wind field within the atmospheric boundary layer height is mainly affected by near-surface radiation, and the simulation height in a small-scale model is generally about 1 km, vertical grid encryption is carried out below 1 km, with 14 layers of encrypted grids set, and the height of the bottommost grid is 25 m. This improves the vertical resolution of the model in the near-surface layer to better transfer effective data to the small-scale wind-temperature coupling model.

[0054] The time integration step is set to 1 s, and the Lambert projection scheme is selected for the map projection during simulation.

[0055] The multi-layer nested grid of the mesoscale model simulation domain is as Figure 2 shown.

[0056] (2) Obtain terrain static data and initial meteorological field data, and configure the physical scheme.

[0057] During the WRF model calculation process, two types of initial data need to be input first, namely terrain static data and initial meteorological field data. The complete three-dimensional initial data within the calculation area is obtained through the built-in integration and interpolation programs of the model. This data is obtained from the open-source websites https: / / www2.mmm.ucar.edu / wrf / users / download / and https: / / rda.ucar.edu / datasets / respectively. The initial meteorological field data needs to select the file for the target simulation period and be loaded in the WRF model. The Yonsei University (YSU) scheme is adopted for the planetary boundary layer scheme, the Rapid Radiative Transfer Model (RRTM) longwave radiation scheme, the Dudhia shortwave radiation scheme, the Goddard microphysics scheme, the Betts-Miller-Janjic cumulus convection parameterization scheme, the Monin-Obukhov (modified MM5) near-surface parameterization scheme, and the Noah land surface process scheme. Among them, the cumulus convection scheme is only enabled for the first layer of the grid. The specific physical scheme parameter settings are shown in Table 1.

[0058] Table 1 Physical scheme parameter settings

[0059]

[0060]

[0061] (3) Establish the geometric model of the small-scale model through 3D modeling software.

[0062] In the small-scale model, the geometric model is divided into a terrain model and a structural model. The process of establishing the terrain model is as follows: Obtain the Digital Elevation Model (DEM) of the bridge site area, import it into the Globalmapper software for slicing processing to obtain the terrain data information of the small-scale simulation domain. Among them, the DEM represents the ground elevation in the form of an ordered numerical array, which contains factors such as elevation, slope, and aspect, and can be obtained through the Geospatial Data Cloud Platform of the Computer Network Information Center of the Chinese Academy of Sciences (http: / / www.gscloud.cn). Since both the spatial position of the mesoscale model and the DEM data adopt the WGS84 coordinate system, the small-scale model adopts the three-dimensional coordinate form of (x, y, z). Therefore, spatial coordinate conversion is required before loading it into the small-scale model, and the formulas are shown as follows (1) - (2). Then, use the three-dimensional modeling software Rhino to establish a terrain surface.

[0063]

[0064] In the formula are the longitude and latitude coordinates in the WGS84 coordinate system, (x, y) are the coordinates in the Mercator projection coordinate system, R is the average radius of the earth, and e is the first eccentricity of the earth ellipsoid.

[0065] The structural model is a solid model established by the three-dimensional modeling software Rhino according to the structural geometric information. The finally established geometric model is as Figure 3 shown.

[0066] (4) According to the morphology of the inlet surface of the small-scale model calculation domain, perform fitting block division and extraction point planning.

[0067] When extracting the results of the mesoscale model, fitting block division and extraction point planning should be carried out first according to the terrain trend and the size of the inlet surface area of the small-scale model. The schematic diagram of the fitting block division of the inlet surface and the distribution of data extraction points is as Figure 4 shown. P1 - P16 only represent the schematic positions of the extraction points, that is, the wind profile and temperature profile of 16 mesoscale results. The number of horizontal and vertical extraction points should be set according to the simulation requirements. Especially on the complex canyon terrain with large terrain undulations, the wind profiles of this quantity can reflect good accuracy effects in the boundary assignment of the small-scale model in the geometric height coordinate system, and to a certain extent, solve the boundary wind speed distortion problems such as too high surface wind speed and missing wind speed values generally existing in the model inlet setting.

[0068] (5) Through the mesoscale model, use the Cressman interpolation method to extract the inlet wind speed and temperature data, and use the least squares method for fitting to obtain the wind speed and temperature functions of the small-scale model inlet surface.

[0069] Since the accuracy of the D03 simulation area of the mesoscale wind-temperature coupling model is 1 km, when extracting data of the required points from the result file, the point may not be exactly located at the grid center or grid point, but at a certain position within the grid. Therefore, it is necessary to obtain the wind speed and temperature data corresponding to the required data extraction points through spatial data interpolation methods.

[0070] The Cressman interpolation method is a grid point value calculation method. Its basic idea is to multiply all the observed values around the interpolation point by a weight coefficient, and then use the weight value to divide the space as a unit step function. This method is easy to implement and calculate, can consider the influence of direction and distance at the same time, can better handle small samples and irregularly distributed data, and is less sensitive to isolated values compared with some other interpolation algorithms. Generally speaking, it has the significant advantages of simplicity and high efficiency.

[0071] The calculation formula is as follows:

[0072]

[0073] In the formula, w ij is the weight between the interpolation point and the observation point, d ij is the Euclidean distance between the interpolation point and the observation point, D is the step function jump threshold, v i represents the interpolation result of the interpolation point, v j represents the observed value of the sample point, and n represents the number of sample points.

[0074] The least squares method is used for function approximation of the extracted data to obtain the fitting function of the inlet surface. The implementation process of the least squares method is shown in the following example. Given the data α0(x), α1(x), …, α n (x), it is necessary to find the function in the function class that minimizes the sum of squared errors as shown in Equation (5) The obtained function is the least squares solution of this function class for this set of data. This process can be implemented using Matlab software.

[0075]

[0076] (6) According to the material properties of the bridge structure, load the geometric model and the wind speed and temperature functions of the inlet surface, establish a small-scale model using the CFD method, and solve the environmental wind, temperature field and structural response.

[0077] The geometric model is meshed using ANSYS software. The geometric model is imported into ANSYS software, and further processing of the geometric model is carried out in the SpaceClaim module. First, the surface quality of the model is checked and repaired. Then, data coupling interaction is established between the two contact surfaces of the fluid and the solid. Next, the boundary surfaces are grouped, and then the meshing is carried out in the Fluentmeshing module. The entire model uses tetrahedral unstructured meshes. Due to the large undulation of the terrain in the computational domain, the wind field in the near-surface boundary layer is highly sensitive to the terrain, and the scale of the bridge tower is relatively small compared to the size of the overall model. Therefore, the terrain boundary, the bridge tower structure, and the fluid domain nearby are meshed with finer grids. The height of the first layer of grids on the terrain surface is 0.1 m, and the boundary layer growth rate is 1.1.

[0078] The meshing situation is as Figures 5 to 8 shown.

[0079] A small-scale model is established using the CFD software Fluent. When setting the inlet boundary conditions, the velocity inlet (Velocity-inlet) and the temperature inlet (Temperature-inlet) are selected. Their initial information is read and set by writing a UDF (User Define Function) program through the fitted inlet surface wind speed and temperature functions. The fluid is considered to be fully developed at the outlet, and the north side of the computational model is set as the pressure outlet boundary (Pressure-outlet). The ground surface and the bridge tower structure surface of the computational model are set as the non-slip wall boundary (Non-slip Wall); the top surface and the east-west side boundary surfaces of the model are set as the symmetry boundary (Symmetry).

[0080] The FSI (Fluid Structure Interaction) definition between the structural wall boundary and the spatial domain is carried out.

[0081] For the calculation, a pressure-based steady-state solver suitable for low-speed incompressible flow is selected. The turbulence model and the turbulence solution scheme select the SST k-ω and SIMPLEC algorithms. The discretization format selects the second-order upwind scheme, and the standard wall function is selected.

[0082] The schematic diagram of the solution parameters is as Figure 9 shown.

Claims

1. A downscaling numerical simulation method for bridge wind-temperature coupling considering real terrain, characterized in that It includes the following steps: (1) Determine the calculation area of the mesoscale model according to the geographical location of the bridge, and adopt multi-layer grid nesting to improve the calculation accuracy; (2) Obtain the terrain static data and the initial meteorological field data, and configure the physical scheme; (3) Establish the geometric model of the small-scale model through 3D modeling software; (4) According to the morphology of the inlet surface of the small-scale model calculation domain, carry out fitting block division and extraction point planning; (5) Through the mesoscale model, use the Cressman interpolation method to extract the inlet wind speed and temperature data, and use the least square method for fitting to obtain the wind speed and temperature functions of the inlet surface of the small-scale model; (6) According to the characteristics of the bridge structure material, load the geometric model and the inlet surface wind speed and temperature functions, use the CFD method to establish the small-scale model, and solve the environmental wind, temperature field and structural response.

2. A downscaling numerical simulation method for bridge wind-temperature coupling considering real terrain according to claim 1, characterized in that The specific method of step (1) is: Adopt a 3-layer bidirectional nested grid scheme for simulation. The 3-layer bidirectional nested grids are d01, d02, and d03 respectively. The horizontal resolutions of the grids from the outside to the inside are 9 km, 3 km, and 1 km respectively, that is, the grid spacing of the outermost d01 grid is 9 km; the number of vertical grids in the calculation domain is set to 50 layers, the top pressure in the model is set to 5000 Pa, and the default bottom pressure in the mesoscale model is 1000 Pa; vertical grid encryption is carried out below 1 km, and 14 layers of encrypted grids are set, and the height of the bottommost grid is 25 m; The time integration step is set to 1 s, and the Lambert projection scheme is selected for the map projection during simulation.

3. A downscaling numerical simulation method for bridge wind-temperature coupling considering real terrain according to claim 1, characterized in that, The specific method of step (2) is: During the calculation process of the WRF model, two types of initial data need to be input first, namely the terrain static data and the initial meteorological field data, and the complete three-dimensional initial data within the calculation area is obtained through the integral and interpolation programs built into the model; the data of the initial meteorological field needs to select the file of the target simulation period and be loaded in the WRF model; the planetary boundary layer scheme adopts the YSU scheme, the RRTM long-wave radiation scheme, the Dudhia short-wave radiation scheme, the Goddard microphysical process scheme, the Betts-Miller-Janjic cumulus convection parameterization scheme, the Monin-Obukhov surface layer parameterization scheme, and the Noah land surface process scheme. Among them, only the cumulus convection scheme is enabled for the first layer of grid.

4. A downscaling numerical simulation method for bridge wind-temperature coupling considering real terrain according to claim 1, characterized in that The specific method of step (3) is: The geometric model in the small-scale model is divided into a terrain model and a structural model; the establishment process of the terrain model is as follows: obtain the digital elevation model DEM of the bridge site area, import it into the Globalmapper software for slicing processing to obtain the terrain data information of the small-scale simulation domain; the small-scale model adopts the (x, y, z) three-dimensional coordinate form; spatial coordinate transformation needs to be carried out before loading it into the small-scale model, and the formulas are shown as follows (1) - (2); then use the 3D modeling software Rhino to establish the terrain surface; where are the longitude and latitude coordinates in the WGS84 coordinate system, (x, y) are the coordinates in the Mercator projection coordinate system, R is the average radius of the earth, and e is the first eccentricity of the earth ellipsoid; The structural model is a solid model established by the 3D modeling software Rhino according to the structural geometric information.

5. A downscaling numerical simulation method for bridge wind-temperature coupling considering real terrain according to claim 1, characterized in that The specific method of step (4) is as follows: When extracting the results of the mesoscale model, first perform the fitting block division and extraction point planning according to the terrain trend and the size of the entrance surface area of the small-scale model.

6. The numerical simulation method for downscaling bridge wind-temperature coupling considering real terrain according to claim 1, characterized in that The calculation formula of the Cressman interpolation method in step (5) is as follows: where w ij is the weight between the interpolation point and the observation point, d ij is the Euclidean distance between the interpolation point and the observation point, D is the step function jump threshold, v i represents the interpolation result of the interpolation point, v j represents the observed value of the sample point, and n represents the number of sample points; The least squares method is used for function approximation of the extracted data to obtain the fitting function of the entrance surface; the implementation process of the least squares method is as follows: Given data α0(x), α1(x), …, α n (x), it is necessary to find the function in the function class of such that the sum of squared errors shown in Equation (5) is minimized. When n ≤ m, the obtained function is the least-squares solution of this function class for this set of data:

7. A downscaling numerical simulation method for bridge wind-temperature coupling considering real terrain according to claim 1, characterized in that The specific method of step (6) is as follows: Use ANSYS software to perform mesh division on the geometric model; import the geometric model into ANSYS software, and perform further processing of the geometric model in the SpaceClaim module. First, check and repair the surface quality of the model, then establish data coupling interaction between the two contact surfaces of the fluid and the solid, then group the boundary surfaces, and then enter the Fluent meshing module for mesh division; the entire model uses tetrahedral unstructured meshes; the terrain boundary, the pylon structure and the nearby fluid domain are meshed more densely; the height of the first layer of mesh on the terrain surface is 0.1 m, and the boundary layer growth rate is 1.1; Use the CFD software Fluent to establish a small-scale model. When setting the inlet boundary conditions, select the velocity inlet and the temperature inlet, and its initial information is set by reading the UDF program written according to the fitted inlet surface wind speed and temperature function; the fluid is regarded as fully developed at the outlet, and the north side of the calculation model is set as the pressure outlet boundary; the ground and pylon structure surfaces of the calculation model are set as non-slip wall boundaries; the top surface and the east-west side boundaries of the model are set as symmetric boundaries; Define the FSI between the structural wall boundary and the spatial domain; Select the pressure-based steady-state solver applicable to low-speed incompressible flow for calculation, select the SST k-ω and SIMPLEC algorithms for the turbulence model and the turbulence solution scheme, select the second-order upwind scheme for the discretization format, and select the standard wall function.

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