A simulation method for wind and light analysis in a multi-medium environment
By establishing a multi-media environment model and combining data acquired by UAVs and ground-based laser scanners, a comprehensive analysis of wind, solar, and thermal effects is conducted. This solves the problem that the multi-media impacts were not considered in existing technologies, achieves high-precision simulation, and improves the accuracy of weather forecasts and renewable energy assessments.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- THE THIRD CONSTR OF CHINA CONSTR EIGHTH ENG BUREAU
- Filing Date
- 2026-03-05
- Publication Date
- 2026-07-03
AI Technical Summary
Existing meteorological models cannot effectively consider the influence of multiple media such as water and soil when simulating urban environments, resulting in inaccurate predictions of wind, solar, and thermal conditions, which affects the accuracy of weather forecasts and renewable energy assessments.
Building image data was acquired using UAVs and ground-based laser scanners to establish a multi-media environment model. Wind analysis was performed using computational fluid dynamics methods, combined with photothermal analysis. The interaction of media such as air, water, and soil was comprehensively considered, and a modular model was used for simulation.
It enables high-precision simulation of the dynamic changes of wind, light, and heat in multi-media environments, improving the accuracy of weather forecasts and renewable energy assessments, and supporting scientific research and practical applications.
Smart Images
Figure CN122334067A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of computer simulation technology, specifically a simulation method for wind, solar and thermal analysis in multi-media environments. Background Technology
[0002] Against the backdrop of climate change and accelerated urbanization, the interaction between wind, light, and heat is having an increasingly significant impact on global climate and local environments. Traditional meteorological models typically consider only the effects of a single medium, such as focusing solely on changes in wind speed and temperature in the air, while neglecting the influence of other media such as water bodies and soil. These limitations lead to significant discrepancies between model predictions and actual observations, affecting the accuracy of weather forecasts and the effectiveness of their practical applications.
[0003] Taking the urban heat island effect as an example, in urban areas, the choice of building materials and the degree of green coverage significantly affect the local climate. Traditional models, when simulating these phenomena, often fail to consider water evaporation, soil heat transfer, and air temperature changes in a unified manner, leading to inaccurate assessments of the urban thermal environment. Similarly, in renewable energy assessments, neglecting the interactions between different media results in biased predictions of wind and solar energy potential. Therefore, a novel simulation model is urgently needed that can comprehensively consider the complex interactions of multiple media to improve the accuracy and practicality of simulations.
[0004] Rapid urbanization and industrialization have exacerbated global warming, making climate change an increasingly serious issue. Against this backdrop, understanding and simulating the dynamic changes of wind, solar, and thermal processes in multi-media environments has become particularly important. Existing models are often limited by spatial resolution and computational power, making it difficult to simultaneously consider the interactions of multiple physical processes. Therefore, developing an efficient and accurate simulation model is of great significance for addressing climate change, optimizing urban planning, and improving the quality of the ecological environment. Summary of the Invention
[0005] In view of the above-mentioned prior art, the present invention proposes a simulation method for wind, solar and thermal analysis in multi-media environments.
[0006] This invention provides a simulation method for wind, solar, and thermal analysis in multi-media environments, comprising the following steps: S1. Model Concept: The environment is divided into multiple layers, each corresponding to a different medium, including: air layer, water layer, and soil layer. S2. Model Building: A multi-lens drone equipped with several lenses is used to acquire image data of the buildings or building areas to be analyzed. The horizontal overlap of each photo is greater than 70%, and the vertical overlap is set according to the time interval of the drone's up and down flight. A ground laser scanner is used to scan the point cloud data of the buildings or building areas. Multiple stations are set up around the area by measuring the first and second overlaps. The real-scene model is built by stitching the point cloud data with software. S3. Multi-media analysis: Perform multi-media analysis based on the model, including wind analysis and light and heat analysis; the wind analysis includes dividing the real-world model into meshes; S4. Overall Summary: The data images from the multi-media analysis are summarized and integrated with the real-world model, allowing observation of the impact of different media on buildings or building areas through the real-world model.
[0007] Preferably, in S1, the air layer includes: bottom boundary layer: 0-2000m, middle layer: 2000-10000m, and upper layer: above 10000m.
[0008] Preferably, in S1, the soil layer includes: topsoil layer: 0-10cm, root layer: 10-30cm, and a deep layer below 30cm.
[0009] Preferably, in S2, the distance between the multiple stations is set to 20m, the point accuracy is maintained at 2.9mm, and the point cloud data acquisition resolution is selected as 6mm@10m.
[0010] Preferably, in S3, the wind analysis is performed by solving the wind field using computational fluid dynamics, that is, establishing mathematical governing equations for the conservation of mass, momentum, and energy of the fluid flow within the analyzed computational domain, as shown below: in, φ This can be expressed as velocity, turbulent kinetic energy, turbulent dissipation rate, or temperature.
[0011] Preferably, in S3, the photothermal analysis includes calculating the radiation amount on the horizontal plane and the radiation amount on the vertical plane, wherein the calculation of the radiation amount on the horizontal plane includes calculating the total radiation intensity on the horizontal plane and the direct radiation intensity on the horizontal plane. The formula for calculating the total radiation intensity of the horizontal plane is: The formula for calculating the direct radiation intensity of the horizontal plane is: Where S0 is the vertical radiance, h is the solar altitude angle, and f and c are empirical parameters; The formula for calculating the vertical plane radiation is: S0 = S·cosh·cos(a-β) Where a is the solar azimuth angle, β is the wall azimuth angle, h is the solar altitude angle, S is the direct radiation flux on the horizontal plane, β=0° for the south-facing wall, β=-90° for the east-facing wall, and β=90° for the west-facing wall.
[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides a simulation method for wind, light and heat analysis in a multi-media environment. The model constructed by this method can comprehensively consider the interaction and physical characteristics of buildings with various media such as wind, light and heat, thereby accurately simulating the dynamic changes of wind, light and heat in complex environments, and providing reliable support for scientific research and practical applications.
[0013] Furthermore, this invention integrates various physical processes and interactions by constructing a modular multi-media environment model, providing a comprehensive perspective for understanding and predicting environmental changes. The core concept of the model design is to treat each medium as an interconnected whole, emphasizing their dynamic interactions, thereby achieving higher simulation accuracy. Attached Figure Description
[0014] Figure 1 This is a real-world model diagram from Embodiment 1 of the present invention.
[0015] Figure 2 This is a three-dimensional digital model diagram in Embodiment 1 of the present invention.
[0016] Figure 3 This is a diagram illustrating the impact of wind on buildings in Embodiment 1 of the present invention.
[0017] Figure 4 This is a diagram showing the effect of light on buildings in Embodiment 1 of the present invention.
[0018] Figure 5 This is a diagram illustrating the impact of heat on buildings in Embodiment 1 of the present invention. Detailed Implementation
[0019] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below with reference to specific embodiments.
[0020] Example 1: As Figures 1-5 The simulation method for wind, solar and thermal analysis in a multi-media environment, as shown, includes the following steps: S1. Model Concept: This model divides the environment into multiple layers, each corresponding to a different medium, including: Air Layer: The model subdivides the air layer into multiple altitude layers to simulate variations in wind speed, temperature, humidity, and air pressure with altitude. Typically, the air layer can be divided into three parts: the lower boundary layer (0-2000m), the middle layer (2000-10000m), and the upper layer (above 10000m). Meteorological elements at different altitudes are affected by different air pressures, temperatures, and wind speeds, therefore these factors must be considered in the calculations.
[0021] Water layer: Represents the depth and temperature distribution of a water body, simulating changes in heat conduction, evaporation, and light intensity. The depth of the water layer typically depends on the topography and water type, such as rivers, lakes, or oceans. The model also considers the effects of biological and chemical reactions within the water body on heat and light intensity.
[0022] Soil layer: Considering the influence of soil thermal conductivity, moisture content, and plant growth, it reflects the dynamic changes in soil moisture. The soil layer can be further subdivided into the topsoil layer (0-10cm), root zone (10-30cm), and deep layer (below 30cm). Different soil layers have different physical properties, such as water retention capacity and thermal conductivity.
[0023] S2. Model Building: An unmanned aerial vehicle (UAV) equipped with five lenses is used to acquire image data of the analyzed building or building area. The horizontal overlap of each photo is greater than 70%, and the vertical overlap is set according to the time interval of the UAV's up and down flight. A terrestrial laser scanner (TLS) is used to scan the point cloud data of the building or building area. Multiple stations are set up around the building using a first-to-last coincidence stitching measurement method. The distance between multiple stations is set to 20m, the point accuracy is maintained at 2.9mm, and the point cloud data acquisition resolution is selected as 6mm@10m. The real scene model is built by stitching the point cloud data using software.
[0024] S3. Multi-media analysis: Perform multi-media analysis based on the model, including wind analysis and photothermal analysis; In wind analysis, the real-world model is meshed. Mesh size determines the accuracy of the calculation and affects the calculation speed. A mesh that is too dense will decrease calculation speed and waste computational resources; a mesh that is too sparse will result in insufficient accuracy. A reasonable meshing scheme needs to consider using different meshing schemes for different parts of the computational domain. Different meshing schemes are required for areas around buildings, areas far from buildings, areas with obvious local features in the building outline (such as sharp corners, recesses, protrusions, and other subtle external decorations), and areas close to the ground.
[0025] Wind analysis is calculated based on the following methods: The wind field is solved using CFD (Computational Fluid Dynamics) methods, which involves establishing mathematical governing equations for the conservation of mass, momentum, and energy of the fluid flow within the analyzed computational domain. The equations are shown below: in, φ These can be physical quantities such as velocity, turbulent kinetic energy, turbulent dissipation rate, and temperature, as shown in Table 1: Table 1. Governing equations for computational fluid dynamics The SIMPLE algorithm is used to solve the above equations. The wind speed amplification factor reflects the amplification effect of high-rise buildings on wind speed, typically referring to the ratio of the maximum wind speed at 1.5m above ground around the building to the wind speed at the same height in an open area. The wind speed amplification factor can be calculated using the following formula: an exponential function of average wind speed with height. in: This is the wind speed amplification factor; The maximum wind speed at a height of 1.5m above the ground around the building is obtained through the aforementioned wind speed calculation and corresponds to the data in the wind speed cloud map at a height of 1.5m. Wind speed at a height of 1.5m above the ground in an open area away from buildings; For open areas away from buildings, the wind speed at a height of 10m above the ground is taken as the wind speed at the boundary of the outdoor wind field inlet. This is the surface roughness index.
[0026] This model is calculated using Swirl wind environment simulation software and the results are visualized.
[0027] In photothermal analysis, the amount of radiation on the horizontal surface is calculated: The total radiation intensity on the horizontal plane is calculated using the Kastelov formula: The formula for calculating the direct radiation intensity on a horizontal plane is: Where S0 is the vertical radiance, h is the solar altitude angle, and f and c are empirical parameters.
[0028] The above two formulas for calculating hourly total solar radiation and direct radiation intensity only require determining the values of two parameters, f and c, which is relatively simple. An empirical relationship between f, c, and water vapor pressure has been established. By fitting the values of f and c using the water vapor pressure values, the total solar radiation and direct radiation on sunny days across the country can be accurately retrieved, and the national distribution of monthly average radiation can be given.
[0029] Using total and direct radiation data from 66 primary radiation stations across China from 1978 to 1985, sunny days with cloud cover less than 2 mm in January were selected, and the average direct and total radiation for January was calculated. The daily average f-values and c-values for sunny days in January at each station were then calculated using the total radiation formula. Since the f-values and c-values change slowly throughout the day, the daily average values can be used to calculate the total and hourly total radiation. Parametric formulas for the January f-values and c-values were established based on water vapor pressure and station altitude. f = 0.151 + 0.072In(1 + e) - 0.013InH c = 0.335 + 0.152In(1 + e) - 0.028InH Where e is the vapor pressure and H is the altitude. The above two equations were fitted using clear-day data from 66 stations over several days before and after the Great Cold solar term. The F-values for the fitted parameters f and c were 33.860 and 21.215, respectively. Referring to the F-distribution table, F values greater than F0.05, indicating a good regression effect. Using the fitted f and c parameters to calculate the total daily radiation and direct radiation, the average relative error between the calculated values and the observed values was less than 5%.
[0030] The above two formulas were used to calculate the f and c values for the Great Cold Day at 704 stations across the country. The f and c values for January in some cities are shown in Table 2.
[0031] Table 2 January f and c values for some cities The parameters f and c characterize the transparency of the atmosphere on a clear day. The smaller the values of f and c, the stronger the atmosphere's ability to transmit total or direct radiation, and they are closely related to the water vapor content and aerosol conditions in the air. In my country, the values of f and c generally decrease from south to north and from low to high altitudes during winter. This is because the higher the latitude and altitude, the lower the water vapor content in the air, and the higher the atmospheric transparency. The Qinghai-Tibet Plateau region has the lowest f and c values due to its dry and thin atmosphere. The Sichuan Basin and its surrounding cities, such as Chongqing and Chengdu, have high values of f and c because of their high aerosol and water vapor content and high water vapor mixing height, resulting in stronger atmospheric attenuation of solar radiation.
[0032] For buildings, the radiation from vertical walls needs to be considered. The formula for direct radiation flux from vertical walls can be used to derive the formulas for direct radiation from walls facing different directions: S0 = S·cosh·cos(a-β) Where a is the solar azimuth angle, β is the wall azimuth angle, h is the solar altitude angle, and S is the direct radiation flux to the horizontal plane.
[0033] The south-facing wall has β=0°, and has S0,0 =S · cosh · cosa The east-facing wall has an angle of β = -90°. S0,-90 =-S · cosh · sina The west-facing wall has an angle of β=90°. S0,90= S · cosh · sina The formula for the intensity of solar radiation on a clear day perpendicular to the direction of sunlight can be obtained as follows: The formula for the direct radiation intensity of the south wall on a sunny day can then be obtained: Formulas for direct radiation intensity on sunny days for the east and west walls: The north wall receives no direct solar radiation in winter, so it is not included in the calculation. From the above two formulas, the total hourly direct solar radiation for the east, south, and west walls on a clear day during the coldest period of winter can be calculated. Adding the two hours with the highest radiation yields the maximum direct radiation for each wall orientation over those two hours. The total solar radiation reaching the wall is Q. t , by direct radiation S t Scattered radiation D t and reflected radiation R t composition: Q t =S t +D t +R t Among them, the scattered radiation D t Using an isotropic mode, if the shading of other buildings is not considered, i.e. Where D0 is the horizontal surface scattered radiation, which is obtained by subtracting the horizontal surface direct radiation from the total horizontal surface radiation.
[0034] Reflected radiation R t Using the formula for reflection radiation on slopes, we obtain: Where r0 is the reflected radiation from the flat ground in front of the slope, α is the slope, and the vertical slope is 90°, therefore R t That is, half of the radiation reflected from flat ground. When the solar altitude angle is high, the reflectivity is usually around 0.2, therefore R t We uniformly take 10% of the total radiation. This can be simplified to: Applying the above formula, the maximum total radiation intensity of the wall surface facing each direction for 2 hours can be calculated using the trapezoidal method.
[0035] Ladybug, a weather simulation plugin based entirely on the Grasshopper platform, is used to intuitively express data analysis and real-world models.
[0036] S4. Overall Summary: All wind, solar and thermal analysis data and images are summarized and integrated with the real-world model, allowing observation of the impact of different media on buildings or building areas through the real-world model.
[0037] Example 2: Renewable energy assessment using the simulation method of Example 1: Study area: A region with abundant wind and solar energy resources, covering an area of 100 km², with complex terrain was selected.
[0038] Input data settings: Wind speed data: The average annual wind speed is 5 m / s, and the wind direction is mainly concentrated at 90° (east) and 270° (west).
[0039] Solar radiation: The average annual radiation intensity is 1800W / m².
[0040] Topographic parameters: The elevation difference varies greatly, with a maximum elevation difference of 300m.
[0041] Simulation process: The model in Example 1 is run to assess the wind and solar energy potential of the region and analyze the feasibility of renewable energy development. The model will comprehensively consider the influence of topography on wind speed and the influence of solar radiation angle on solar energy.
[0042] Results Analysis: Simulation results show that the region's wind energy utilization rate reaches as high as 30% in winter and is lower in summer, making it suitable for wind energy development. Analysis of wind speed and direction variations can provide a scientific basis for wind farm site selection. Regarding solar energy, the long sunshine hours and high radiation intensity in summer are suitable for large-scale solar photovoltaic power generation. Combining meteorological data with annual forecasts of photovoltaic power generation potential can support the formulation of renewable energy policies.
[0043] The above are merely embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent solutions made using the contents of the present invention specification, whether directly or indirectly applied to other related technical fields, are similarly within the patent protection scope of the present invention.
Claims
1. A simulation method for wind, solar, and thermal analysis in multi-media environments, characterized in that, Includes the following steps: S1. Model Concept: The environment is divided into multiple layers, each corresponding to a different medium, including: air layer, water layer, and soil layer. S2. Model Building: A multi-lens drone equipped with several lenses is used to acquire image data of the buildings or building areas to be analyzed. The horizontal overlap of each photo is greater than 70%, and the vertical overlap is set according to the time interval of the drone's up and down flight. A ground laser scanner is used to scan the point cloud data of the buildings or building areas. Multiple stations are set up around the area by measuring the first and second overlaps. The real-scene model is built by stitching the point cloud data with software. S3. Multi-media analysis: Perform multi-media analysis based on the model, including wind analysis and light and heat analysis; the wind analysis includes dividing the real-world model into meshes; S4. Overall Summary: The data images from the multi-media analysis are summarized and integrated with the real-world model, allowing observation of the impact of different media on buildings or building areas through the real-world model.
2. The simulation method for multi-media environmental wind, solar, and thermal analysis as described in claim 1, characterized in that, In S1, the air layer includes: bottom boundary layer: 0-2000m, middle layer: 2000-10000m, and upper layer: above 10000m.
3. The simulation method for multi-media environment wind, solar and thermal analysis as described in claim 1 or 2, characterized in that, In S1, the soil layer includes: topsoil layer: 0-10cm, root layer: 10-30cm, and deep layer below 30cm.
4. The simulation method for multi-media environment wind, solar and thermal analysis as described in claim 1 or 2, characterized in that, In S2, the distance between the multiple stations is set to 20m, the point accuracy is maintained at 2.9mm, and the point cloud data acquisition resolution is selected as 6mm@10m.
5. The simulation method for multi-media environment wind, solar and thermal analysis as described in claim 1 or 2, characterized in that, In S3, the wind analysis is performed by solving the wind field using computational fluid dynamics methods. That is, mathematical governing equations for the conservation of mass, momentum, and energy of fluid flow are established within the analyzed computational domain, and their forms are shown below: in, φ This can be expressed as velocity, turbulent kinetic energy, turbulent dissipation rate, or temperature.
6. The simulation method for multi-media environment wind, solar and thermal analysis as described in claim 1 or 2, characterized in that, In S3, the photothermal analysis includes calculating the radiation amount on the horizontal plane and the radiation amount on the vertical plane. The calculation of the radiation amount on the horizontal plane includes calculating the total radiation intensity on the horizontal plane and the direct radiation intensity on the horizontal plane. The formula for calculating the total radiation intensity of the horizontal plane is: The formula for calculating the direct radiation intensity of the horizontal plane is: Where S0 is the vertical radiance, h is the solar altitude angle, and f and c are empirical parameters; The formula for calculating the vertical plane radiation is: S0 = S·cosh·cos(a-β) Where a is the solar azimuth angle, β is the wall azimuth angle, h is the solar altitude angle, S is the direct radiation flux on the horizontal plane, β=0° for the south-facing wall, β=-90° for the east-facing wall, and β=90° for the west-facing wall.