Urban thermal comfort simulation method for coupling vegetation heat humidity and radiation effect based on open source framework

Abstract

The invention discloses an open source framework-based urban thermal comfort simulation method for coupling vegetation thermal humidity and radiation effects, which is characterized in that a reproducible, extensible and end-to-end urban outdoor thermal comfort simulation method is constructed on a completely open source tool chain, an open source CFD solver, a grid tool and a Python-based radiation and thermal comfort calculation library are taken as cores, and the open source CFD solver, the grid tool and the Python-based radiation and thermal comfort calculation library are taken as the core. A scripted data pipeline is adopted to realize all-day dynamic outdoor thermal comfort simulation of coupled vegetation heat humidity and radiation effect; according to the method, the open source tool chain and the scripted data pipeline are taken as the core, the modeling and example cost is reduced on the premise of keeping the integrity of the key physical process, and the reproducibility is enhanced.

Description

Technical Field

[0001] This invention relates to the field of outdoor thermal comfort simulation technology, specifically to an urban thermal comfort simulation method based on an open-source architecture that couples the thermal and humid effects of vegetation with radiation. Background Technology

[0002] Outdoor thermal comfort simulation is a crucial link connecting urban climate mechanisms with spatial design decisions. For planning and design, reliable thermal comfort assessment is not only related to thermal health and public safety, but also directly affects the optimization decisions and cost-effectiveness of urban form design. The evapotranspiration and radiation effects of vegetation significantly affect microscale thermal comfort. If the thermal and humid effects of plants are not coupled during the thermal comfort simulation process, systematic deviations may occur in the direction and magnitude of intervention effects.

[0003] Computational fluid dynamics (CFD) plays a crucial role in analyzing airflow and heat transport at the pedestrian scale. Although complete blade energy balance models can be embedded in CFD, custom development programs are often required, resulting in high implementation costs. Therefore, many studies simplify vegetation thermal forcing, such as setting a fixed volumetric cooling rate or estimating evapotranspiration using the Penman–Monteith formula. However, transpiration cooling is constrained by ambient relative humidity and coupled with flow and radiation fields. Without a dynamic solution for the blade energy balance, it is difficult to accurately capture the thermal and moisture feedback process.

[0004] In coupling CFD with outdoor thermal comfort, common practices only input wind speed and air temperature into the comfort model while ignoring the moisture term, and rarely consider the contribution of vegetation to longwave and shortwave radiation in human radiation flux. The dedicated microclimate software ENVI-met is widely used due to its integration of vegetation-radiation-comfort indices, but it still faces challenges such as difficulties in verifying grid independence, simplification of turbulence parameterization, and high costs associated with commercial licensing and computational power. These factors hinder its widespread application and rapid solution evaluation. Summary of the Invention

[0005] Purpose of the Invention: The purpose of this invention is to provide an urban thermal comfort simulation method based on an open-source architecture that couples the thermal and humidity effects of vegetation with radiation. On an open-source toolchain, it integrates the coupling process of air-solid-vegetation thermal and humidity balance in CFD, as well as the influence of plant canopy on human thermal radiation flux. Without sacrificing accuracy, it reduces radiation ergonomics and data integration overhead, improves solution convergence stability and parallel efficiency, and explicitly characterizes the combined effects of vegetation evapotranspiration, shading, long and short wave radiation, and aerodynamic drag, thus solving the problems existing in the background technology.

[0006] Technical Solution: The present invention provides a method for simulating urban thermal comfort based on an open-source architecture and coupling vegetation heat and humidity with radiation effects, comprising the following steps: S1: A 3D geometry-generated mesh based on buildings, surfaces, vegetation, and the solution domain, where the air domain uses a Cartesian mesh, and the solid domain is generated by extruding the outer surface to form walls, surface materials, and soil domains. S2: Input the thermal and optical properties of the materials, the biophysical and optical parameters of the vegetation, and generate an hourly table of solar position and radiation, and meteorological boundary conditions; S3: Run the microclimate coupled solver to solve the radiation field, flow field, blade energy balance and solid field in sequence at each time step. Generate a sampling surface at pedestrian height and perform triangulation. Extract and interpolate air temperature, wind speed, relative humidity and ground temperature at the sampling points. S4: Perform hemispherical ray projection in scenes with vegetation and scenes without vegetation, redistribute the first intersection statistics based on vegetation transmittance, obtain three types of visual factors: sky, buildings and vegetation, and calculate the direct exposure ratio of the human body. S5: Based on the apparent factor, temperature and emissivity of various surfaces, synthesize long-wave and short-wave radiation components and calculate the average radiation temperature; S6: Calculate physiological equivalent temperature using mean radiant temperature, air temperature, relative humidity, and wind speed as inputs; S7: Read physiological equivalent temperature results and surface boundary data, generate regular interpolation grids and visualize them.

[0007] Further, step S1 is as follows: using a general-format 3D geometry as input; using an open-source meshing tool to perform Cartesian meshing on the air domain, with the air domain using a multi-layer nested mesh and the wall boundaries using a layered refinement setting; using an open-source tool to extrude the outer surface to generate a solid domain.

[0008] Furthermore, step S2 specifically involves: assigning material thermal and optical parameters to the solid domain and its surface, and assigning biophysical and optical parameters to the vegetation and its surface; generating an hourly solar position table based on an open-source library; constructing an hourly inflow and radiation-driven boundary condition table in conjunction with meteorological data; and loading the parameters and boundary conditions into the corresponding regions of the microclimate coupled solver.

[0009] Further, step S3 is as follows: run the microclimate coupled solver in the open source solver in a multi-core parallel manner; perform equal area triangulation on the ground and move the triangulation network to the pedestrian height; form a point set with the centroid of the triangulation as the sampling point; interpolate the obtained three-dimensional field data on the sampling point; calculate the average temperature of the vegetation surface and the average temperature of the building surface in the entire computational domain.

[0010] Furthermore, in step S4, calculating the visual factor and the direct human exposure ratio specifically involves: reading the pedestrian layer sampling point set and the triangular mesh geometry of buildings and vegetation, and establishing a fast query index to accelerate intersection determination; generating a sky hemispherical direction set, and uniformly generating ray directions for each sampling point; performing hemispherical ray projection on both the vegetation-containing and vegetation-free scenes respectively, and statistically analyzing the initial occlusion ratios of the sky, buildings, and vegetation; considering the difference in the initial occlusion ratios of buildings in the two scenes as the share of building directions intercepted by vegetation, and allocating the transmitted portion according to the vegetation transmittance. The building visual factor is included, and the remainder is included in the vegetation visual factor. The difference between the initial sky occlusion ratios of the two scenes is considered as the share of the sky direction intercepted by vegetation. The transmitted portion is included in the sky visual factor according to the vegetation transmittance, and the remainder is included in the vegetation visual factor. The sum of the three types of visual factors is one to obtain the final visual factors of each element considering vegetation occlusion and transmission. The sun direction is obtained according to the time step, human representative points are set up at the sampling points, and the proportion of no occlusion is calculated after occlusion is determined to obtain the proportion of direct human exposure. The results table of visual factors and direct human exposure ratio is output.

[0011] Further, step S5 specifically involves: reading the apparent factor result table and the microclimate data table, and aligning and stitching them according to the time step; calculating the horizontal component of long-wave sky radiation based on air temperature and relative humidity; synthesizing the surface equivalent temperature according to the apparent factor weights based on the building average temperature, vegetation average temperature, and surface temperature; calculating the long-wave equivalent temperature difference and short-wave equivalent temperature difference using the equivalent surface temperature, long-wave sky radiation, solar altitude angle, direct and diffuse radiation intensity, sky exposure, and human direct exposure ratio as inputs, and synthesizing the average radiation temperature; and outputting a summary table of the average radiation temperature for each spatial point.

[0012] Furthermore, assuming that the upper hemisphere of the apparent factor consists of the sky, buildings, and vegetation, while the lower hemisphere is the ground, the average radiation temperature is calculated based on the human net radiation energy flux model that takes into account the influence of solar radiation.

[0013] Furthermore, step S6 is as follows: using average radiation temperature, air temperature, relative humidity, and wind speed as inputs, combined with configurable human body parameters; calculating the physiological equivalent temperature of each sampling point at each time step based on the human body thermal balance model; and using an open-source library to complete the calculation and output the results.

[0014] Furthermore, S7 specifically performs the following steps: reads the summary table of physiological equivalent temperature results and site boundary data; generates a regular grid within the effective point envelope; performs two-dimensional interpolation on the physiological equivalent temperature and draws an isopleth map; and exports the image file.

[0015] An electronic device according to the present invention includes a memory and a processor. The memory stores a computer program, and the processor executes the program to implement the steps of the method.

[0016] Beneficial Effects: Compared with existing technologies, this invention has the following significant advantages: It uses an open-source toolchain and scripted data pipeline as its core, reducing modeling and computational costs and enhancing reproducibility while maintaining the integrity of key physical processes; it explicitly couples the thermal, humidity, and wind speed fields of the CFD output caused by the vegetation thermal and humidity effect after iterative convergence with outdoor thermal comfort calculations, avoiding systematic biases in thermal comfort calculations driven solely by wind speed and air temperature; in the calculation of visual factors, it decomposes the simulation into a secondary model by superimposing vegetated and non-vegetated scenes, reducing the number of radiation traversals and improving solution efficiency; it naturally supports hourly and multi-scenario batch processing and parallel acceleration throughout the day, significantly shortening the scheme evaluation time; and it is compatible with standard meteorological data and common 3D geometric formats, facilitating cross-project migration and extended applications. Attached Figure Description

[0017] Figure 1 This is a flowchart of the present invention; Figure 2 This is a schematic diagram of the solid domain extrusion generation geometry of the present invention; Figure 3 This is a simplified schematic diagram of the method for calculating visual factors involving vegetation according to the present invention; Figure 4 This is a schematic diagram illustrating the PET calculation of pedestrian height at 8:00 AM according to the present invention; Figure 5 This is a schematic diagram illustrating the pedestrian height PET calculation at 14:00 according to the present invention; Figure 6 This is a schematic diagram illustrating the pedestrian height PET calculation at 18:00 according to the present invention. Detailed Implementation

[0018] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0019] like Figure 1 As shown, this embodiment of the invention provides a method for simulating urban thermal comfort based on an open-source architecture that couples vegetation heat and humidity with radiation effects, including the following steps: S1 generates a mesh based on the 3D geometry of the building, surface, vegetation, and solution domain. The air domain uses a Cartesian mesh, while the solid domain is generated by extruded from the outer surface, forming walls, surface materials, and soil. Specifically: The 3D geometry of the building, surface, vegetation, and the solution domain is constructed using Rhino and exported as an STL file. The open-source meshing tool cfMesh is used to create a Cartesian mesh for the air domain, employing a three-layer nested mesh. The wall boundaries are densely packed with a layered expansion coefficient. OpenFOAM's extrudeMesh tool is used to extrude the outer surface to generate the solid domain mesh for walls, surface materials, and soil. The wall mesh is 0.3 meters wide, and the surface materials and soil mesh are 2 meters wide. An expansion coefficient of 1.2 is used during extrusion. Figure 2 As shown.

[0020] S2, input material thermal and optical parameters, vegetation biophysical and optical parameters, and generate hourly solar position and radiation, meteorological boundary condition tables; the specific process is as follows: assign material thermal and optical parameters to the solid domain and its surface, and assign biophysical and optical parameters to the vegetation body and its surface; generate hourly solar position tables based on Python's pvlib library; combine the temperature and relative humidity data of the meteorological station and the radiation data of a typical meteorological year (TMY) to construct hourly inflow and radiation-driven boundary condition tables; load the above parameters and boundary conditions into the corresponding regions of the microclimate coupled solver.

[0021] S3 runs the microclimate coupled solver, solving the radiation field, flow field, blade energy balance, and solid field sequentially at each time step. A sampling surface is generated at a pedestrian height of 1.5m, and equal-area triangulation is performed. Air temperature, wind speed, relative humidity, and the ground temperature corresponding to the point projection are extracted and interpolated using the centroid of the triangle as the sampling point. Specifically: In OpenFOAM, the `mpirun` command is used to run `urbanMicroclimateFoam` in parallel across multiple cores to solve for various microclimate parameters in the solution domain; equal-area triangulation of the ground geometry is performed based on Grasshopper, and the entire triangulation network is copied to a pedestrian height of 1.5m; OpenFOAM's post-processing tool `sample` is used to form a point set using the centroid of each triangle as the sampling point; the obtained three-dimensional fields of air temperature, wind speed, relative humidity, and ground temperature are interpolated at the above sampling points; and OpenFOAM's post-processing tool `surfaceFieldValue` is used to calculate the average surface temperature of vegetation and the average surface temperature of buildings throughout the entire computational domain.

[0022] S4, hemispherical ray casting is performed in both scenes with and without vegetation. The first intersection statistics are redistributed based on the vegetation transmittance τ to obtain three types of view factors: sky, buildings, and vegetation. Specifically: the pedestrian layer sampling point set and the triangular mesh geometry of buildings and vegetation are read, and accelerated structures for ray-triangular mesh intersections are constructed for both. In Python, the Tregenza sky hemispherical direction set provided by the ViewSphere module of the Ladybug library is called to uniformly generate ray directions for each sampling point. Ray directions are then generated for scenes with and without vegetation. Hemispherical ray projection was performed on two scenes, one with vegetation and one without, and the initial occlusion ratios of the sky, buildings, and vegetation were statistically analyzed. The difference in the initial occlusion ratio of buildings in the two scenes was considered as the share of the building direction intercepted by vegetation. The transmitted portion was included in the building visual factor according to the vegetation transmittance, and the remainder was included in the vegetation visual factor. The difference in the initial occlusion ratio of the sky in the two scenes was considered as the share of the sky direction intercepted by vegetation. The transmitted portion was included in the sky visual factor according to the vegetation transmittance, and the remainder was included in the vegetation visual factor. The sum of the three visual factors was one to obtain the final visual factors of each element considering vegetation occlusion and transmission, such as... Figure 3 As shown; the sun's position is obtained by time step and converted into a sun direction vector. Five human representative points are evenly distributed along the height of the human body at each sampling point. Building and vegetation occlusion are determined sequentially along the sun direction. The proportion of unobstructed human representative points is counted to obtain the proportion of direct human exposure. The time step, sampling point coordinates, three types of visual factors and the proportion of direct human exposure are output as a result table.

[0023] S5. Based on the apparent factors, temperatures, and emissivity of various surfaces, long-wave and short-wave radiation components are synthesized to calculate the equivalent radiation temperature and obtain the mean radiation temperature (MRT). Specifically, the process involves: reading the apparent factor and direct human exposure result table and the CFD merge table output from step S4 in Python, and aligning and stitching the two tables according to time steps; calculating the dew point temperature based on air temperature and relative humidity, and obtaining the horizontal component of the sky's long-wave radiation accordingly; and synthesizing the surface equivalent temperature based on the building average temperature, vegetation average temperature, and the ground temperature corresponding to the spatial point projection, weighted according to the apparent factor. The model assumes that the upper hemisphere of the apparent factor consists of the sky, buildings, and vegetation, while the lower hemisphere consists entirely of the ground. Using equivalent surface temperature, horizontal longwave radiation, solar altitude angle, direct and diffuse radiation intensity, sky exposure, and the proportion of direct human exposure as inputs, the model calls the outdoor_sky_heat_exch() function of the ladybug_comfort library in Python to calculate the longwave equivalent temperature difference, shortwave equivalent temperature difference, and synthesize the average radiation temperature. This function is based on the SolarCal human net radiation energy flux model that considers the influence of solar radiation.

[0024] Align air temperature, relative humidity, wind speed, and mean radiant temperature by time step, and output a summary table in CSV format for each spatial point.

[0025] S6 calculates the physiological equivalent temperature (PET) using MRT, air temperature, relative humidity, and wind speed as inputs, and outputs the hourly results throughout the day. Using the average radiation temperature from step S5 and the air temperature, relative humidity, and wind speed from step S3 as inputs, and combining configurable human body parameters, the PET of each sampling point at each time step is calculated based on the physiological equivalent temperature model of human body thermal balance. The PET calculation is performed in Python by calling the physiologic_equivalent_temperature() function of the ladybug_comfort library, and the thermal comfort level is calculated by calling the pet_category_humid() function.

[0026] S7 reads the PET results summary table and surface boundary vector data, filters records by specified time, generates a regular interpolation grid for scattered point coordinates within the boundary, and uses interpolation methods to generate PET raster for visualization. Specifically: In Python, read the PET results summary table of spatial points in CSV format and the site boundary in Shapefile format; within the envelope of valid points, generate a regular grid using numpy.linspace() and numpy.meshgrid(); perform two-dimensional interpolation on the PET data using scipy.interpolate.griddata(), and use matplotlib.pyplot.contourf() to draw an isoplethogram, exporting the image file, such as... Figure 4 , 5 As shown in Figure 6.

Claims

1. A method for simulating urban thermal comfort based on open source framework coupled with vegetation thermal and moisture effects, characterized in that, The method comprises the following steps: S1: generating a grid based on the three-dimensional geometry of buildings, ground surfaces, vegetation bodies, and a solution domain, wherein a Cartesian grid is used for the air domain, and a solid domain is generated by extruding the outer surface to form wall bodies, ground surface materials, and soil domains; S2: inputting material thermal physical and optical parameters, vegetation biophysical and optical parameters, and generating a table of hourly solar position and radiation, meteorological boundary conditions; S3: running a microclimate coupling solver to sequentially solve a radiation field, a flow field, a leaf energy balance, and a solid field at each time step, generating a sampling surface at a pedestrian height and performing triangulation, and extracting and interpolating air temperature, wind speed, relative humidity, and ground temperature at sampling points; S4: performing hemispherical ray casting on a scene containing vegetation and a scene without vegetation, respectively, redistributing the first interaction statistics according to the vegetation transmittance to obtain sky, building, and vegetation view factors, and calculating the direct exposure ratio of the human body; S5: synthesizing long-wave and short-wave radiation components according to the view factors, temperatures, and emissivities of various surfaces to calculate the average radiant temperature; S6: calculating the physiological equivalent temperature by inputting the average radiant temperature, air temperature, relative humidity, and wind speed; S7: reading the physiological equivalent temperature result and the ground boundary data, generating a regular interpolation grid, and visualizing the grid.

2. The urban thermal comfort simulation method of claim 1, wherein, Step S1 is specifically as follows: a three-dimensional geometry in a common format is used as input; an open-source grid division tool is used to divide the air domain into a Cartesian grid, and a multi-layer nested grid is used for the air domain, and a layered encryption setting is used for the wall boundary; an open-source tool is used to extrude the outer surface to generate the solid domain.

3. The urban thermal comfort simulation method of coupling vegetation thermal and moisture effects with radiation effects based on open-source framework according to claim 1, characterized in that, Step S2 is specifically as follows: material thermal physical and optical parameters are assigned to the solid domain and its surface, and biophysical and optical parameters are assigned to the vegetation body and its surface; a table of hourly solar position is generated based on an open-source library; a table of hourly inflow and radiation driving boundary conditions is constructed in combination with meteorological data; and the parameters and boundary conditions are loaded into the corresponding regions of the microclimate coupling solver.

4. The urban thermal comfort simulation method of coupling vegetation thermal and moisture effects with radiation effects based on open-source framework according to claim 1, characterized in that, Step S3 is specifically as follows: the microclimate coupling solver is run in a multi-core parallel mode in the open-source solver; equal-area triangulation is performed on the ground surface, and the triangular mesh is moved to a pedestrian height; a point set is formed by taking the barycentric points of the triangulated mesh as sampling points; The three-dimensional field data obtained by solving is interpolated at the sampling points; and the average temperature of the vegetation surface and the average temperature of the building surface of the entire calculation domain are calculated.

5. The urban thermal comfort simulation method of coupling vegetation thermal and moisture effects with radiation effects based on open-source framework according to claim 1, characterized in that, In step S4, the calculation of the view factor and the human direct exposure ratio is as follows: reading the pedestrian layer sampling point set and the triangular net geometry of the building and vegetation, and establishing a fast query index to speed up the intersection determination; generating a set of sky hemisphere directions, and uniformly generating ray directions for each sampling point; performing hemispherical ray projection on the two scenes containing vegetation and without vegetation respectively, and counting the first occlusion ratio of the sky, building, and vegetation; regarding the difference between the first occlusion ratios of the building in the two scenes as the building direction share intercepted by the vegetation, and integrating the penetrated part into the building view factor according to the vegetation transmittance, and counting the remaining part into the vegetation view factor; regarding the difference between the first occlusion ratios of the sky in the two scenes as the sky direction share intercepted by the vegetation, and integrating the penetrated part into the sky view factor according to the vegetation transmittance, and counting the remaining part into the vegetation view factor; the sum of the three types of view factors is one, and the final view factor of each element considering the vegetation occlusion and transmission is obtained; obtaining the sun direction according to the time step, arranging a human representative point at the sampling point, determining the unoccluded ratio after occlusion, and obtaining the human direct exposure ratio; outputting the view factor and the human direct exposure ratio result table.

6. The urban thermal comfort simulation method of coupling vegetation thermal and moisture effects with radiation effects based on open-source framework according to claim 1, characterized in that, In step S5, the specific operation is as follows: reading the view factor result table and the microclimate data table, and aligning and splicing according to the time step; calculating the sky long-wave radiation horizontal component based on the air temperature and the relative humidity; synthesizing the surface equivalent temperature according to the view factor weight based on the building average temperature, the vegetation average temperature, and the ground temperature; Taking the equivalent surface temperature, the sky long-wave radiation, the solar elevation angle, the direct and scattered radiation intensity, the sky exposure degree, and the human direct exposure ratio as inputs, the long-wave equivalent temperature difference and the short-wave equivalent temperature difference are calculated, and the average radiation temperature is synthesized; outputting the average radiation temperature total table of each space point.

7. The urban thermal comfort simulation method of coupling vegetation thermal and moisture effects with radiation effects based on open-source framework according to claim 6, characterized in that, It is assumed that the upper hemisphere of the view factor is composed of the sky, the building, and the vegetation, and the lower hemisphere is the ground; The average radiation temperature is calculated based on the human net radiation energy flux model considering the influence of solar radiation.

8. The urban thermal comfort simulation method of coupling vegetation thermal and moisture effects with radiation effects based on open-source framework according to claim 1, characterized in that, In step S6, the specific operation is as follows: taking the average radiation temperature, the air temperature, the relative humidity, and the wind speed as inputs, and combining the configurable human parameters; calculating the physiological equivalent temperature of each sampling point at each time step based on the human heat balance model; The open source library is used to complete the calculation and output the results.

9. The urban thermal comfort simulation method of coupling vegetation thermal and moisture effects with radiation effects based on open-source framework according to claim 1, characterized in that, In step S7, the specific operation is as follows: reading the physiological equivalent temperature result total table and the site boundary data; generating a regular grid within the effective point envelope range; performing two-dimensional interpolation on the physiological equivalent temperature, and drawing an isofill color map; exporting an image file.

10. An electronic device, comprising: The memory stores a computer program, and the processor executes the program to realize the steps of the method of claims 1-9.

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