A method and system for urban microclimate fluid dynamics simulation incorporating vegetation

Abstract

The application discloses a kind of urban microclimate fluid dynamics simulation method and system of vegetation binding, wherein method steps are: establishing solution domain and carrying out multi-scale nested grid division;Building and ground surface multi-layer material grid division;Definition tree crown, grassland and each ground surface material area grid;Definition air domain and the initial field and boundary condition of each different material solid domain;With discrete coordinate method (fvDOM) calculation solar radiation and long-wave radiation transfer in solution domain;Iterative solution vegetation canopy internal leaf energy balance equation;Solution vegetation canopy internal air velocity, turbulence, temperature and humidity source term;Based on the fluid-solid coupling solution of steady-state RANS equation and result output.The urban microclimate fluid dynamics simulation method and system by the aerodynamic and radiation, latent heat and convection heat transfer effect process of vegetation modeling, thereby realize the influence of urban vegetation in urban microclimate simulation, compared with existing tool, the prediction of hot, humid environment is more comprehensive, and the thermal interaction of vegetation and building, ground surface material is fully considered;When simulating large-scale urban area, through multi-layer nested grid division, the calculation efficiency is significantly improved.

Description

Technical Field

[0001] This invention relates to a method and system for simulating urban microclimate fluid dynamics, and more particularly to a method and system for simulating urban microclimate fluid dynamics by combining a vegetation model. Background Technology

[0002] Climate change and its adverse effects are a major challenge facing the international community, and the continuous expansion of urbanization globally is one of the main causes of climate change. The urban environment alters the geometries, materials, vegetation, water resources, and human activities of a region, profoundly impacting local climates. The urban heat island effect refers to the phenomenon where temperatures within cities are higher than in surrounding rural areas, and surface albedo, vegetation evapotranspiration, and anthropogenic heat sources are the main factors contributing to the climate differences between urban and rural areas. The urban heat island effect negatively impacts human health and comfort and significantly increases building energy consumption in summer. Urban vegetation effectively reduces surface and air temperatures in surrounding urban areas through evapotranspiration and shading, and is therefore gradually becoming a feasible strategy for mitigating the urban heat island effect. To fully utilize available resources, urban planners need to predict the impact of urban vegetation on urban microclimates and develop effective strategies to mitigate the urban heat island effect.

[0003] Fluid dynamics is an important tool for predicting the impact of urban morphology on urban microclimates, but a comprehensive fluid dynamics model for urban microclimates that fully considers the thermal effects of urban vegetation is still lacking. Current fluid dynamics research mostly focuses on the aerodynamic effects of vegetation, neglecting the sensible and latent heat contributions of vegetation to the microclimate. Some studies simulate the thermal effects of vegetation by adding temperature source terms to the temperature equation, but existing methods still have shortcomings. First, most existing fluid dynamics modeling methods involving vegetation thermal effects only include the sensible heat effects of vegetation, neglecting or only roughly considering the latent heat effects, such as estimating latent heat using empirically obtained volumetric cooling rates. Second, existing methods ignore the complex interactions between urban vegetation, urban buildings, and surface materials. Specifically, they fail to consider the long-wave radiation transfer between obstacles such as buildings and vegetation canopies and the shading effect on short-wave radiation, and ignore the impact of sensible heat transfer between air and surface materials and building surfaces on air temperature. Therefore, when simulating complex three-dimensional urban environments, this leads to significant errors in the simulation results. Summary of the Invention

[0004] Purpose of the invention: To provide a method and system for simulating urban microclimate fluid dynamics by combining urban vegetation, which can realize the modeling of urban vegetation in the simulation of urban microclimate fluid dynamics in a three-dimensional model, and fully consider the contribution of vegetation in radiation, convection heat transfer and latent heat.

[0005] Technical solution: The urban microclimate fluid dynamics simulation method combining urban vegetation models described in this invention includes the following steps:

[0006] Step 1: Establish the solution domain and perform mesh generation with nested meshes at three scales;

[0007] Step 2: Import the geometric model of the urban area's buildings and surface materials, and perform unstructured mesh generation;

[0008] Step 3: Define the grid for the canopy area, grassland area, and various surface material areas;

[0009] Step 4: Define the initial field and boundary conditions for the air domain and the solid domains of different materials;

[0010] Step 5: Calculate the propagation of solar radiation and longwave radiation in the solution domain using the discrete coordinate method (fvDOM) to obtain the radiation distribution within the canopy volume, on the building surface, and on the ground surface;

[0011] Step 6: Using a custom C++ library, iteratively solve the leaf energy balance equation inside the vegetation canopy and output the leaf surface temperature of the vegetation.

[0012] Step 7: Using a custom C++ library, solve for the source terms of air velocity, turbulence, temperature, and humidity within the vegetation canopy;

[0013] Step 8: Solve the fluid-structure interaction of the air domain and the surface material layer based on the steady-state RANS equations, and output the microclimate simulation results.

[0014] As a further constraint on the method, the specific steps in step 1 for establishing the solution domain and performing three-scale nested mesh generation are as follows:

[0015] Step 1.1, the maximum vertical distance between buildings in the simulated urban area is defined as H. max The established solution domain extends 5 times H to the windward, vertically upward, and on both sides of the simulated urban area. max The downwind direction expands to 15 times the height. max ;

[0016] Step 1.2: The nested mesh is divided into three sizes. The mesh size of the entire solution domain is 16m*16m, the middle mesh size is 8*8m, ​​and the smallest mesh size is 4m*4m. The smallest mesh area covers the geometric model of the simulated urban area.

[0017] As a further constraint on the method, in step 2, the specific steps for generating the urban geometric unstructured mesh are as follows:

[0018] Step 2.1: Import the building and the geometric models of the three types of ground surfaces—asphalt, concrete, and grass—in STL format;

[0019] Step 2.2: Refine the mesh on the surfaces of the building and ground geometry model entities;

[0020] Step 2.3: Extrude the surface material downwards to generate a solid model with a depth of 2m. Define the depth of the first layer mesh as 0.1m and the expansion ratio as 1.2.

[0021] As a further refinement of the method, in step 3, when defining the grids for the canopy region, grassland region, and various surface material regions, the specific steps are as follows:

[0022] Step 3.1: Filter the grids in the air region. Grids whose volume is more than 1 / 2 located inside the canopy of vegetation (excluding grassland) are defined as canopy regions.

[0023] Step 3.2: On the grass-covered surface, the adjacent air grid above the surface is set as the grass area, and the depth from 0m to 2m below the surface is defined as soil.

[0024] Step 3.3: For artificial paved surfaces, a depth of 0.2m below the surface is defined as the paving material (asphalt or concrete), and a depth of 0.2m to 2m below the surface is defined as soil;

[0025] Step 3.4: Assign leaf area density values ​​to the tree canopy and grassland respectively, and establish them as constant fields.

[0026] As a further refinement of the method, in step 4, the boundary conditions of the air region and the building surface are calculated using the following heat balance formula, combining Newton's law of cooling, solid heat conduction, and surface heat radiation:

[0027]

[0028] In the formula, κ is the air heat transfer coefficient; q r R is the external radiative heat flux of the building. th The total thermal resistance of the wall to convective heat transfer between the wall and the building interior, and to conductive heat transfer within the wall; T i T represents the temperature of the air inside the building. e The external air temperature of the building; T w δ represents the external surface temperature of the building; δ represents the distance from the center point of the adjacent air grid of the wall to the building surface.

[0029] As a further refinement of the method, in step 5, when calculating the propagation of solar radiation and longwave radiation in the solution domain using the discrete coordinate method (fvDOM), the radiation intensity within the spatial solid angle is converted into the radiation intensity G on the plant leaf surface using the following formula. leaf :

[0030] G leaf =G-4*σSB *T 4

[0031] In the formula, G is the radiation intensity within the solid angle of space; σ SB is the Boltzmann constant; T is the air temperature.

[0032] As a further constraint on the method, in step 6, the leaf energy balance equation of the vegetation canopy within the grid volume is:

[0033] q rad，leaf -q lat，leaf -q sen，leaf =0

[0034] In the formula, q rad，leaf q represents the radiative flux across the leaf surface. lat，leaf The latent heat flux over the leaf surface; q sen，leaf Let q be the convective heat flux over the leaf surface. The latent heat flux of the leaf blade is q. lat，leaf Calculated using the following formula:

[0035]

[0036] In the formula, L v R is the latent heat of vaporization; ρ is the air density; p is the air pressure; a R is the gas constant for dry air; v r is the gas constant of water vapor; a For aerodynamic drag; r s p represents pore resistance. v，leaf p is the vapor pressure at the blade. v It is the vapor pressure of air.

[0037] As a further limitation of the method, in step 7, when calculating the source terms of air velocity, turbulence, temperature, and humidity within the vegetation canopy, the specific steps are as follows:

[0038] Step 7.1, calculate the velocity source term S of the air within the vegetation canopy using the following formula. u :

[0039]

[0040] In the formula, c d LAD is the drag coefficient of the plant canopy; LAD is the leaf area density. This represents the speed value.

[0041] Step 7.2, calculate the turbulence source term S of the air within the vegetation canopy using the following formula. x and S e :

[0042]

[0043]

[0044] In the formula, β p β d C e C e κ is a constant, ε is the turbulent kinetic energy, and ε is the turbulent dissipation rate.

[0045] Step 7.3, calculate the temperature source term S of the air within the vegetation canopy using the following formula. T :

[0046]

[0047] Step 7.4, calculate the humidity source term S of the air within the vegetation canopy using the following formula. w :

[0048]

[0049] In the formula, g v，leaf This represents the steam mass flux.

[0050] This invention also provides an urban microclimate fluid dynamics simulation system that combines a vegetation model, characterized by: a custom function built based on the open-source fluid dynamics software OpenFOAM and written in C++, including a preprocessing module and an iteration module, and determining whether to output the result based on whether the result of the iterative simulation module converges;

[0051] The preprocessing module is used to create nested meshes for the solution domain, import urban geometric models, divide the model mesh, and set the initial field and boundary conditions for the solution domain.

[0052] The iteration module is used for iterative solutions of fluid dynamics based on the RANS equations, solving for the fields in the air domain and the surface solid domain of multilayer materials;

[0053] After the iterative simulation module completes its calculation at the current time step, it uses the residual to determine whether the simulation has converged. If convergence is achieved, the result is output; otherwise, it proceeds to the next time step.

[0054] The simulation results include momentum, pressure, density, temperature, humidity, radiation, leaf surface radiation, and leaf surface temperature in the air domain, as well as temperature in the solid domain.

[0055] As a further constraint on the system, the specific steps for performing the solution in the iterative simulation module are as follows:

[0056] At the beginning of each time step in the simulation module, the initial field information of the current time step is read first;

[0057] Add a velocity source term for the air within the plant canopy, and solve and write the velocity field into the air domain;

[0058] Add a temperature source term for the air within the plant canopy, and solve and write the temperature field into the air domain;

[0059] Solve for and write the radiation field into the air domain;

[0060] Solve for and write the pressure field in the air domain;

[0061] Add a humidity source term for the air within the plant canopy, and solve and write the humidity field into the air domain;

[0062] Add turbulence source terms for air within the plant canopy, and solve and write the turbulence field into the air domain;

[0063] Solve and record the temperature of the ground solid domain of multilayer materials;

[0064] The blade temperature field is solved iteratively by using the blade energy balance equation, the result is written into the system, and the number of steps for the equation to converge is indicated.

[0065] Compared with existing technologies, the beneficial effects of this invention are: (1) It considers the radiation, latent heat and convective heat transfer effects of vegetation at the same time, and the prediction of thermal and humid environment is more comprehensive than existing tools; (2) It fully considers the mutual radiation shielding and transmission effects of vegetation, buildings and ground; (3) It considers the convective heat transfer of outdoor air and indoor air of buildings and the heat conduction of walls; (4) It considers the heat conduction of solid materials with different thermal properties inside the ground surface and the convective and radiative heat transfer between the ground surface and the air; (5) Based on open source fluid dynamics programs and custom C++ libraries, the basic code library is easy to obtain and the subsequent functions are highly extensible; (6) Using multi-layer nested meshes, the computational efficiency is significantly improved when simulating large-scale urban areas. Attached Figure Description

[0066] Figure 1 This is a schematic diagram of the overall process of the present invention;

[0067] Figure 2 This is a schematic diagram illustrating the multi-layer material division of the earth's surface according to the present invention;

[0068] Figure 3 This is a schematic diagram of the thermal balance of the building wall according to the present invention;

[0069] Figure 4 This is a schematic diagram of the simulation system structure of the present invention. Detailed Implementation

[0070] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the embodiments described.

[0071] like Figure 1As shown, the urban microclimate fluid dynamics simulation method combining vegetation models described in this invention includes the following steps:

[0072] Step 1: Establish the solution domain and perform mesh generation with nested meshes at three scales;

[0073] The specific steps for establishing the solution domain and performing nested mesh generation at three scales are as follows:

[0074] The maximum vertical distance between buildings in the simulated urban area is defined as H. max The established solution domain extends 5 times H to the windward, vertically upward, and on both sides of the simulated urban area. max The downwind direction expands to 15 times the height. max ;

[0075] The nested mesh is divided into three sizes: the mesh size of the entire solution domain is 16m*16m, the middle mesh size is 8*8m, ​​and the smallest mesh size is 4m*4m. The smallest mesh area covers the geometric model of the simulated urban area.

[0076] By extending the model in all directions, especially downwind, the adaptation and evolution of airflow in the computational domain can be fully considered, reducing the impact of boundary effects and improving simulation stability. Through multiple mesh nesting, computational resource waste can be minimized while maintaining the accuracy of the simulation in the region of interest, thus improving computational speed.

[0077] Step 2: Import the geometric model of the urban area's buildings and surface materials, and perform unstructured mesh generation;

[0078] The specific steps for performing urban geometric unstructured mesh generation are as follows:

[0079] Import 3D geometric models of buildings and surface materials in STL format;

[0080] Refine the mesh on the surfaces of building and ground geometry models;

[0081] The surface material is extruded downwards to generate a solid model with a depth of 2m. The depth of the first layer mesh is defined as 0.1m, and the expansion ratio is 1.2. Figure 2 As shown.

[0082] By refining the surface of buildings and the ground, the accuracy of mesh simulation near the entity can be improved, and the spatial impact of buildings and the ground on microclimate can be fully considered; by dividing underground materials into multiple layers, the variation of heat flux in the vertical direction can be considered.

[0083] Step 3: Define the grid for the canopy area, grassland area, and various surface material areas;

[0084] The specific steps for defining the grids for canopy areas, grassland areas, and various surface material areas are as follows:

[0085] The grids in the air region are filtered, and grids whose volume is more than 1 / 2 located inside the canopy of vegetation (excluding grassland) are defined as canopy regions;

[0086] The grass-covered surface is defined as the adjacent air grid above the surface as the grass area, and the depth from 0m to 2m below the surface is defined as soil.

[0087] For artificially paved surfaces, a depth of 0.2m below the surface is defined as the paving material (asphalt or concrete), and a depth of 0.2m to 2m below the surface is defined as soil. Figure 2 As shown;

[0088] The leaf area density of the tree canopy and the grassland is assigned values ​​respectively, and these are established as constant fields.

[0089] Spatial topology methods can be used to quickly select grassland and vegetation areas, enabling the rapid construction of vegetation models in large-scale cities. By forming sets of different types of vegetation grids, it is easier to solve for the air source terms of the canopy of various types of vegetation in iterative simulations.

[0090] Step 4: Define the initial field and boundary conditions for the air domain and the solid domains of different materials;

[0091] The initial field and boundary of the fluid region include momentum, pressure, density, temperature, humidity, radiation, leaf area density, leaf surface radiation, and leaf surface temperature.

[0092] like Figure 3 As shown, the boundary conditions of the air region and the building surface are calculated using the following heat balance formula, combining Newton's law of cooling, solid heat conduction, and surface heat radiation:

[0093]

[0094] In the formula, κ is the air heat transfer coefficient; q r R is the external radiative heat flux of the building. th The total thermal resistance of the wall to convective heat transfer between the wall and the building interior, and to conductive heat transfer within the wall; T i T represents the temperature of the air inside the building. e The external air temperature of the building; T w δ represents the external surface temperature of the building; δ represents the distance from the center point of the adjacent air grid of the wall to the building surface.

[0095] Step 5: Calculate the propagation of solar radiation and longwave radiation in the solution domain using the discrete coordinate method (fvDOM) to obtain the radiation distribution within the canopy volume, on the building surface, and on the ground surface;

[0096] When calculating the propagation of solar radiation and longwave radiation in the solution domain using the discrete coordinate method (fvDOM), the radiation intensity within the spatial solid angle is converted into the radiation intensity G on the plant leaf surface using the following formula. leaf :

[0097] G leaf =G-4*σ SB *T 4

[0098] In the formula, G is the radiation intensity within the solid angle of space; σ SB is the Boltzmann constant; T is the air temperature.

[0099] Step 6: Using a custom C++ library, iteratively solve the leaf energy balance equation inside the vegetation canopy and output the leaf surface temperature of the vegetation.

[0100] The leaf energy balance equation for the vegetation canopy within the grid volume is:

[0101] q rad，leaf -q lat，leaf -q sen，leaf =0

[0102] In the formula, q rad，leaf q represents the radiative flux across the leaf surface. lat，leaf The latent heat flux over the leaf surface; q sen，leaf Let q be the convective heat flux over the leaf surface. The latent heat flux of the leaf blade is q. lat，leaf Calculated using the following formula:

[0103]

[0104] In the formula, L v R is the latent heat of vaporization; ρ is the air density; p is the air pressure; a R is the gas constant for dry air; v r is the gas constant of water vapor; a For aerodynamic drag; r s p represents pore resistance. v，leaf p is the vapor pressure at the blade. v It is the vapor pressure of air.

[0105] By solving the leaf energy balance equation within the plant canopy, the spatial distribution field of leaf temperature and water vapor mass flux can be obtained, thereby enabling the acquisition of the source terms of the influence of the vegetation canopy on air temperature and humidity, and providing a simulation method for solving the latent heat effect of vegetation.

[0106] Step 7: Using a custom C++ library, solve for the source terms of air velocity, turbulence, temperature, and humidity within the vegetation canopy;

[0107] The velocity source term S of air within the vegetation canopy is calculated using the following formula. u :

[0108]

[0109] In the formula, c d LAD is the drag coefficient of the plant canopy; LAD is the leaf area density. The value is the velocity.

[0110] The turbulence source term S of the air within the vegetation canopy is calculated using the following formula. x and S t :

[0111]

[0112]

[0113] In the formula, β p β d C e C e κ is a constant, ε is the turbulent kinetic energy, and ε is the turbulent dissipation rate.

[0114] The temperature source term S of the air within the vegetation canopy is calculated using the following formula. T :

[0115]

[0116] The humidity source term S within the vegetation canopy is calculated using the following formula. w :

[0117]

[0118] In the formula, g v，leaf This represents the steam mass flux.

[0119] Step 8: Solve the fluid-structure interaction of the air domain and the surface material layer based on the steady-state RANS equations. The solution process is iterative. When the residuals reach the convergence criterion, the simulation results are output.

[0120] like Figure 4 As shown, the present invention also provides an urban microclimate fluid dynamics simulation system that combines a vegetation model, characterized in that: it is based on the open-source fluid dynamics software OpenFOAM and a custom function written in C++, including a preprocessing module and an iteration module, and determines whether to output the result based on whether the result of the iterative simulation module converges;

[0121] The preprocessing module is used to create nested meshes for the solution domain, import urban geometric models, divide the model mesh, and set the initial field and boundary conditions for the solution domain.

[0122] The iteration module is used for iterative solutions of fluid dynamics based on the RANS equations, solving for the fields in the air domain and the surface solid domain of multilayer materials;

[0123] After the iterative simulation module completes its calculation at the current time step, it uses the residual to determine whether the simulation has converged. If convergence is achieved, the result is output; otherwise, it proceeds to the next time step.

[0124] The simulation results include momentum, pressure, density, temperature, humidity, radiation, leaf surface radiation, and leaf surface temperature in the air domain, as well as temperature in the solid domain.

[0125] As a further constraint on the system, the specific steps for performing the solution in the iterative simulation module are as follows:

[0126] At the beginning of each time step in the simulation module, the initial field information of the current time step is read first;

[0127] Add a velocity source term for the air within the plant canopy, and solve and write the velocity field into the air domain;

[0128] Add a temperature source term for the air within the plant canopy, and solve and write the temperature field into the air domain;

[0129] Solve for and write the radiation field into the air domain;

[0130] Solve for and write the pressure field in the air domain;

[0131] Add a humidity source term for the air within the plant canopy, and solve and write the humidity field into the air domain;

[0132] Add turbulence source terms for air within the plant canopy, and solve and write the turbulence field into the air domain;

[0133] Solve and record the temperature of the ground solid domain of multilayer materials;

[0134] The blade temperature field is solved iteratively by using the blade energy balance equation, the result is written into the system, and the number of steps for the equation to converge is indicated.

[0135] After the iterative simulation module completes its calculation at the current time step, it uses the residual to determine whether the simulation has converged. If convergence is achieved, the result is output; otherwise, it proceeds to the next time step.

[0136] The simulation results include momentum, pressure, density, temperature, humidity, radiation, leaf surface radiation, and leaf surface temperature in the air domain, as well as temperature in the solid domain.

[0137] As described above, although the invention has been shown and described with reference to specific preferred embodiments, it should not be construed as limiting the invention itself. Various changes in form and detail may be made without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. A method for simulating urban microclimate fluid dynamics by combining vegetation models, characterized in that, Includes the following steps: Step 1: Expand the solution domain based on the maximum building height in the simulated area, and perform three-level nested mesh generation, with the smallest mesh level covering the geometric model of the simulated urban area; Step 2: Import the geometric model of urban area buildings and various surface materials, refine the mesh of buildings and surface, extend the surface downward to generate multi-layer solid domain entities, and then perform unstructured mesh generation. Step 3: Define the canopy area and grassland area based on the grid spatial location and volume ratio, divide the surface material layer and underlying soil layer into grids, and assign the leaf area density field of the corresponding area. Step 4: Define the initial field and boundary conditions for the air domain and the solid domains of different materials, where the building surface adopts the thermal equilibrium boundary conditions of coupled indoor and outdoor convection heat transfer, wall heat conduction and surface radiation. Step 5: Use the discrete coordinate method to calculate the propagation of solar radiation and longwave radiation in the solution domain, and obtain the radiation distribution within the canopy volume, building surface and ground surface; Step 6: Iteratively solve the leaf energy balance equation inside the vegetation canopy and output the leaf surface temperature of the vegetation. Step 7: Based on the leaf energy balance results, solve for the source terms of air velocity, turbulence, temperature, and humidity within the vegetation canopy; Step 8: Perform fluid-structure interaction iterative solution based on steady-state RANS equations for the air domain and multi-layer surface solid domain. Output microclimate simulation results after iterating until the residuals converge.

2. The urban microclimate fluid dynamics simulation method combining vegetation models according to claim 1, characterized in that, In step 1, the specific steps for establishing the solution domain and performing nested mesh generation at three scales are as follows: Step 1.1, the maximum vertical distance between buildings in the simulated urban area is defined as H. max The established solution domain is the simulated urban area, extended 5 times H upwind, vertically above, and to both sides. max The downwind direction expands to 15 times H max ; Step 1.2: The nested mesh is divided into three sizes. The mesh size of the entire solution domain is 16m*16m, the middle mesh size is 8*8m, ​​and the smallest mesh size is 4m*4m. The smallest mesh area covers the geometric model of the simulated urban area.

3. The urban microclimate fluid dynamics simulation method combining vegetation models according to claim 1, characterized in that, In step 2, the specific steps for generating the urban geometric unstructured mesh are as follows: Step 2.1: Import the building and the geometric models of the three types of ground surfaces (asphalt, concrete, and grass) in st1 format; Step 2.2: Refine the mesh on the surfaces of the building and ground geometry model entities; Step 2.3: Extrude the surface material downwards to generate a solid model with a depth of 2m. Define the depth of the first layer mesh as 0.1m and the expansion ratio as 1.

2.

4. The urban microclimate fluid dynamics simulation method combining vegetation models according to claim 1, characterized in that, In step 3, the specific steps for defining the grids for the canopy area, grassland area, and various surface material areas are as follows: Step 3.1: Filter the grids in the air area. Grids whose volume is more than 1 / 2 located inside the vegetation are defined as canopy areas. Step 3.2: On the grass-covered surface, the adjacent air grid above the surface is set as the grass area, and the depth from 0m to 2m below the surface is defined as soil. Step 3.3: For artificial paving surfaces, a depth of 0.2m below the surface is defined as paving material, and a depth of 0.2m to 2m below the surface is defined as soil; Step 3.4: Assign leaf area density values ​​to the tree canopy and grassland respectively, and establish them as constant fields.

5. The urban microclimate fluid dynamics simulation method combining vegetation models according to claim 1, characterized in that, In step 4, the boundary conditions of the air region and the building surface are calculated using the following heat balance formula, combining Newton's law of cooling, solid heat conduction, and surface heat radiation: In the formula, κ is the air heat transfer coefficient; q r R is the external radiative heat flux of the building. th The total thermal resistance of the wall to convective heat transfer between the wall and the building interior, and to conductive heat transfer within the wall; T i T represents the temperature of the air inside the building. e The external air temperature of the building; T w δ represents the external surface temperature of the building; δ represents the distance from the center point of the adjacent air grid of the wall to the building surface.

6. The urban microclimate fluid dynamics simulation method combining vegetation models according to claim 1, characterized in that, In step 5, when calculating the propagation of solar radiation and longwave radiation in the solution domain using the discrete coordinate method, the radiation intensity within the spatial solid angle is converted into the radiation intensity G on the plant leaf surface using the following formula. leaf : G leaf =G-4*σ SB *T 4 In the formula, G is the radiation intensity within the solid angle of space; σ SB is the Boltzmann constant; T is the air temperature.

7. The urban microclimate fluid dynamics simulation method combining vegetation models according to claim 1, characterized in that, In step 6, the leaf energy balance equation for the vegetation canopy within the grid volume is: q rad,leaf -q lat,leaf -q sen，leaf =0 In the formula, q red，leaf q represents the radiative flux across the leaf surface. lat，leaf The latent heat flux over the leaf surface; q sen，leaf The convective heat flux over the leaf surface; where the latent heat flux of the leaf blade is q. lat,leaf Calculated using the following formula: In the formula, L v R is the latent heat of vaporization; ρ is the air density; p is the air pressure; a R is the gas constant for dry air; v r is the gas constant of water vapor; a For aerodynamic drag; r s p represents pore resistance. v，leaf p is the vapor pressure at the blade. v It is the vapor pressure of air.

8. The urban microclimate fluid dynamics simulation method combining vegetation models according to claim 1, characterized in that, In step 7, the specific steps for calculating the source terms of air velocity, turbulence, temperature, and humidity within the vegetation canopy are as follows: Step 7.1, calculate the velocity source term S of the air within the vegetation canopy using the following formula. u : In the formula, c d LAD is the drag coefficient of the plant canopy; LAD is the leaf area density. The value is the velocity. Step 7.2, calculate the turbulence source term S of the air within the vegetation canopy using the following formula. κ and S ε : In the formula, β p β d C ε C ε κ is a constant, ε is the turbulent kinetic energy, and ε is the turbulent dissipation rate. Step 7.3, calculate the temperature source term S of the air within the vegetation canopy using the following formula. T : Step 7.4, calculate the humidity source term S of the air within the vegetation canopy using the following formula. w : In the formula, g v，leaf This represents the steam mass flux.

9. A system for simulating urban microclimate fluid dynamics by incorporating a vegetation model, characterized in that: A custom function written in C++ based on the open-source fluid dynamics software OpenFOAM includes a preprocessing module and an iteration module, and determines whether to output the result based on whether the result of the iterative simulation module converges. The preprocessing module is used to create nested meshes for the solution domain, import urban geometric models, divide the model mesh, and set the initial field and boundary conditions for the solution domain. The iteration module is used for iterative solutions of fluid dynamics based on the RANS equations, solving for the fields in the air domain and the surface solid domain of multilayer materials; After the iterative simulation module completes its calculation at the current time step, it uses the residual to determine whether the simulation has converged. If convergence is achieved, the result is output; otherwise, it proceeds to the next time step. The simulation results include momentum, pressure, density, temperature, humidity, radiation, leaf surface radiation, and leaf surface temperature in the air domain, as well as temperature in the solid domain.

10. The urban microclimate fluid dynamics simulation system combining a vegetation model according to claim 9, characterized in that: The specific steps for performing the solution in the iterative simulation module are as follows: At the beginning of each time step in the simulation module, the initial field information of the current time step is read first; Add a velocity source term for the air within the plant canopy, and solve and write the velocity field into the air domain; Add a temperature source term for the air within the plant canopy, and solve and write the temperature field into the air domain; Solve for and write the radiation field into the air domain; Solve for and write the pressure field in the air domain; Add a humidity source term for the air within the plant canopy, and solve and write the humidity field into the air domain; Add turbulence source terms for air within the plant canopy, and solve and write the turbulence field into the air domain; Solve and record the temperature of the ground solid domain of multilayer materials; The blade temperature field is solved iteratively by using the blade energy balance equation, the result is written into the system, and the number of steps for the equation to converge is indicated.

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