Building roof rainwater analysis method and device, storage medium and electronic equipment

Abstract

The application discloses a building roof rainwater analysis method and device, a storage medium and an electronic equipment. The method comprises the following steps: establishing a three-dimensional model of a target building roof; determining the rainwater catchment flow, the rain flow thickness and the rainwater load distribution of each region of the target building roof under multiple groups of wind-rain coupling conditions based on the three-dimensional model, multiple groups of wind-rain coupling parameters, the interaction characteristics of raindrop particles and the target building roof, and the physical characteristics of the target building roof, wherein the multiple groups of wind-rain coupling conditions cover the combined scenes of adverse wind directions, extreme wind speeds and extreme rainfall of different return periods in the region where the target building is located, and the parameter values of the wind-rain coupling parameters corresponding to each group of wind-rain coupling conditions are different; determining the envelope extreme value of the target building roof rainwater effect based on the rainwater catchment flow, the rain flow thickness and the rainwater load distribution of each region of the target building roof under the multiple groups of wind-rain coupling conditions; and performing analysis on the rainwater catchment characteristics and the rainwater load of the target building roof based on the envelope extreme value.

Description

Technical Field

[0001] This application relates to the field of building technology, and in particular to a method, apparatus, storage medium and electronic equipment for analyzing rainwater on building roofs. Background Technology

[0002] In existing building roof rainwater analysis, the mainstream method for estimating rainfall and calculating rainwater load uses the roof's horizontal projected area. This method calculates the amount of rainwater collected and the rainwater load based on the roof's horizontal projected area and a preset fixed rainfall intensity coefficient. However, under extreme weather conditions, heavy rainfall and strong winds do not act independently but rather form a synergistic wind-rain coupling effect. That is, extreme wind fields significantly alter the trajectory, angle of fall, and impact intensity of raindrops, disrupting the normal vertical fall of rainwater in calm or low-wind conditions, fundamentally changing the movement patterns and confluence characteristics of rainwater. Existing methods, focusing only on the roof's horizontal projected area and a fixed rainfall intensity coefficient, fail to accurately reflect the movement path and collection patterns of rainwater on the roof, easily leading to underestimation or overestimation of local rainwater loads, ultimately affecting the rationality of building structural design and drainage system configuration. Summary of the Invention

[0003] In view of the above problems, this application provides a method, apparatus, storage medium and electronic device for analyzing rainwater on building roofs.

[0004] To solve the above-mentioned technical problems, this application proposes the following solution:

[0005] Firstly, this application provides a method for analyzing rainwater on building roofs. The method includes: establishing a three-dimensional model of the target building roof; determining the rainwater runoff, rainwater thickness, and rainwater load distribution in each area of ​​the target building roof under multiple rainwater coupling conditions based on the three-dimensional model, multiple sets of wind-rain coupling parameters, the interaction characteristics between raindrop particles and the target building roof, and the physical characteristics of the target building roof; determining the envelope extreme value of the rainwater effect on the target building roof based on the rainwater runoff, rainwater thickness, and rainwater load distribution in each area of ​​the target building roof under multiple wind-rain coupling conditions; and analyzing the rainwater runoff characteristics and rainwater load of the target building roof based on the envelope extreme value.

[0006] Secondly, this application provides a building roof rainwater analysis device, which includes:

[0007] The model building module is used to create a 3D model of the target building's roof.

[0008] The first determination module is used to determine the rainwater runoff, rainwater thickness, and rainwater load distribution of each area of ​​the target building roof under multiple wind and rain coupling conditions based on the three-dimensional model, multiple sets of wind and rain coupling parameters, the interaction characteristics between raindrop particles and the target building roof, and the physical characteristics of the target building roof.

[0009] The second determination module is used to determine the envelope extreme value of the rainwater effect on the roof of the target building based on the rainwater runoff, rainwater thickness and rainwater load distribution in each area of ​​the roof of the target building under multiple sets of wind and rain coupling conditions.

[0010] The analysis module is used to analyze the rainwater runoff characteristics and rainwater load of the target building roof based on the envelope extrema.

[0011] To achieve the above objectives, according to a third aspect of this application, a storage medium is provided, the storage medium including a stored program, wherein, when the program is executed, the device on which the storage medium is located is controlled to perform the building roof rainwater analysis method of the first aspect.

[0012] To achieve the above objectives, according to a fourth aspect of this application, an electronic device is provided, the device including at least one processor, and at least one memory and bus connected to the processor; wherein the processor and memory communicate with each other through the bus; the processor is used to call program instructions in the memory to execute the building roof rainwater analysis method of the first aspect described above.

[0013] By employing the above-described technical solution, the technical solution provided in this application has at least the following advantages:

[0014] This application considers wind-rain coupling parameters when determining the trajectory of raindrop particles and the rainwater runoff in various areas of the roof. Since these parameters reflect the synergistic mechanism of heavy rainfall and strong winds, they can realistically simulate the impact of this synergy on the trajectory and angle of raindrops under extreme weather conditions. This breaks the ideal assumption of vertical rainfall, making the process of raindrops moving from the air to the roof conform to natural laws. In depicting the complete process of rainwater flowing from raindrops in the air to the roof, the interaction characteristics between raindrop particles and the target building's roof are considered. Therefore, the transformation logic after raindrops contact the roof can be clearly defined, ensuring that raindrops do not simply terminate their movement upon impact with the roof, but rather transform into rainwater flowing along the roof surface, guaranteeing the continuity of the rainwater movement path. Based on this, in determining the flow path and collection state of rainwater along the roof, this application considers both the physical characteristics of the target building's roof and relies on its actual geometric conditions based on a three-dimensional model. Therefore, it can directly constrain the movement state of rainwater through the physical characteristics of the roof, and clarify the flow path of rainwater along the roof by combining the geometric features of the three-dimensional model, so that the movement of rainwater conforms to the actual constraints determined by the physical characteristics of the roof. In summary, the roof rainfall analysis of this application can accurately reflect the movement path and collection pattern of rainwater on the roof.

[0015] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0016] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0017] Figure 1 A flowchart illustrating a method for analyzing rainwater on building roofs provided in an embodiment of this application is shown.

[0018] Figure 2 This application provides a schematic diagram of a process for determining the rainwater runoff, rainwater thickness, and rainwater load distribution in each area of ​​the target building roof under each set of wind and rain coupling conditions.

[0019] Figure 3 This illustration shows a structural schematic diagram of a building roof rainwater analysis device provided in an embodiment of this application;

[0020] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0021] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0022] In the embodiments of this application, the terms "first," "second," etc., do not have a logical or temporal dependency, nor do they limit the quantity or execution order. It should also be understood that although the following description uses the terms "first," "second," etc., to describe various elements, these elements should not be limited by the terms. These terms are merely used to distinguish one element from another.

[0023] In this application, the term "at least one" means one or more, and the term "multiple" means two or more.

[0024] It should also be understood that the term “if” can be interpreted as “when” or “upon”, or “in response to determination” or “in response to detection”. Similarly, depending on the context, the phrase “if determination…” or “if detection [the stated condition or event]” can be interpreted as “when determination…” or “in response to determination…” or “when detection [the stated condition or event]” or “in response to detection [the stated condition or event]”.

[0025] The following section provides a detailed explanation of the rainwater analysis method for building roofs, with reference to the accompanying drawings. Figure 1 This application provides a flowchart illustrating a method for analyzing rainwater on building roofs. Specifically, it includes the following steps:

[0026] Step 110: Create a 3D model of the target building's roof.

[0027] With the development of large public buildings, transportation hubs, and stadiums, building roofs are increasingly characterized by large spans, complex structures, significant undulations, and multi-layered or openwork designs. Rainwater runoff and load distribution are becoming increasingly critical to the structural safety and reliable operation of drainage systems. Under extreme weather conditions, rainfall and wind fields do not act independently but rather interact synergistically; this interaction is known as wind-rain coupling. Extreme wind fields alter the trajectory, angle of fall, and impact intensity of raindrops, causing significant differences in the runoff path and volume of rainwater on the roof compared to calm or low-wind conditions. The dynamic combination of rainfall intensity and wind field parameters collectively determines the intensity of rainwater impact on the roof.

[0028] The analysis of rainwater runoff characteristics and rainwater loads on building roofs under such wind and rain coupling effects highly depends on the accurate depiction of the roof's geometry, structural features, and spatial relationships. Traditional simplified calculation methods or two-dimensional models are insufficient to reproduce the true state of complex roofs, easily leading to problems such as distorted wind field calculation boundaries, biased particle trajectory analysis, and inaccurate calculation of runoff. Therefore, this application establishes a three-dimensional model of the target building roof to completely replicate its geometric and structural information.

[0029] When creating a 3D model of the target building's roof, the structural design drawings, roof construction details, slope annotation documents, and spatial location parameters of the target building are used as the basic data sources. Planar coordinates, elevation data, structural dimensions, and slope design values ​​of the roof are extracted from these sources, ensuring the modeling data remains consistent with the actual engineering design parameters. The 3D model fully reproduces the overall shape of the target building's roof, extracting the roof's planar layout boundary coordinates, elevation changes in the spatial outline, transition angles at slope joints, and the length and width parameters of the overall span from the structural design drawings. It replicates the roof's slope distribution characteristics, covering the overall slope design value of the main slope, while refining the slope transition angles, transition lengths, and joint positions of local slope-changing areas. The slope information is completely consistent with the parameters annotated in the design documents.

[0030] For the local structural features of the roof, the model presents key structures such as gutters, drainage ditches, downspouts, parapet walls, ridges, and eaves one by one. Gutters are modeled based on the cross-sectional dimensions, direction coordinates, and connection height with the roof from the detailed structural drawings, clearly defining the inner and outer slopes of the gutter and the bottom drainage slope. Drainage ditches are recreated with their width, depth, design slope, and drainage direction, clearly showing the wall thickness, interface connection type, and connection relationship with gutters or downspouts. Downspouts are marked with their center coordinates, aperture size, thickness and height of the edge reinforcement structure, as well as the connection method and sealing structure with gutters or roofs. Parapet walls, ridges, and eaves are fully recreated with their height, thickness, contour curves, and connection details with the slope, including the coping type of the parapet wall, the ridgeline direction and cross-sectional shape of the ridge, and the overhang length and drainage slope of the eaves. For complex structures such as hollowed-out, multi-layered, locally protruding, or recessed features, their spatial structure is fully recreated using 3D modeling technology. The openwork structure precisely replicates the diameter of the openwork holes, the center-to-center spacing of the holes, the dimensions of the edge reinforcement structure, and the connection relationship between upper and lower layers, clearly defining the boundary coordinates of the openwork area and its relative position to the overall roof. The multi-layered structure clearly defines the thickness of each layer, the alignment coordinates of upper and lower layers, the position and dimensions of the supporting structure, and the connection nodes between layers. Local protrusions or depressions are reproduced with their height or depth, the boundary coordinates of their horizontal projection range, and the transition slope and connection structure with the surrounding roof, clearly defining the connection relationships and boundary coordinates between each structure.

[0031] For complex roofs with significant undulations, multiple slope directions, or clearly defined functional zones, the modeling process involves dividing the roof into zones based on slope differences, structural zoning, or functional uses (e.g., accessible roof areas, equipment roof areas, green roof areas). Specific coordinate ranges are used to define the boundaries of each zone, labeling zone numbers and their affiliations, creating a zone reference table, and linking it to the 3D model in real time. After completing the roof geometry modeling, the roof surface is discretized into a mesh. The mesh scale is dynamically adjusted according to the geometric complexity of each area, with the standard being that the mesh can fully capture local structural details and runoff characteristics: for areas with flat slopes and simple structures, the mesh edge length is set to 0.5m-1.0m; for areas with dense structures and drastic slope changes, the mesh edge length is adjusted to 0.1m-0.3m; and for key water-collecting areas such as near gutters and around drain outlets, the mesh edge length is further refined to 0.05m-0.1m. Each discrete grid is assigned a unique grid ID, which is associated with its partition number, the corresponding actual coordinate range of the roof (X, Y, Z axis coordinate intervals), the structural type of the area (such as gutter grid, slope grid, grid around the drain outlet), and slope parameters, forming a grid attribute data table that is linked with the 3D model in real time.

[0032] Step 120: Based on the three-dimensional model, multiple sets of wind and rain coupling parameters, the interaction characteristics between raindrop particles and the target building roof, and the physical characteristics of the target building roof, determine the rainwater runoff, rainwater thickness, and rainwater load distribution in each area of ​​the target building roof under multiple wind and rain coupling conditions.

[0033] After constructing the 3D model of the target building's roof, the model accurately replicates the roof's geometry, structural features, and spatial relationships. However, the runoff behavior and load distribution of rainwater on the roof are influenced by the combined effects of wind and rain. The dynamic combination of extreme wind fields and rainfall alters the trajectory, angle of fall, and impact intensity of raindrops, leading to complex changes in runoff paths and collection volumes. Simultaneously, the interaction characteristics between raindrop particles and the roof directly determine the transformation method after raindrops contact the roof, and the physical properties of the target building's roof also affect the runoff unit's movement path and runoff efficiency. To accurately reflect the true movement and collection characteristics of rainwater on complex roofs, this application, based on the precise fundamental data provided by the 3D model, combined with wind-rain coupling parameters, the interaction characteristics between raindrop particles and the target building's roof, and the physical properties of the target building's roof, determines the rainwater runoff flow rate, rainwater thickness, and rainwater load distribution in each area of ​​the target building's roof under each wind-rain coupling condition.

[0034] Specifically, step 210: Based on the 3D model and wind-rain coupling parameters, determine the wind-rain coupled two-phase flow field within the computational domain of the target building and its roof. Step 220: Based on the wind-rain coupled two-phase flow field, determine the trajectory of raindrop particles, and based on the trajectory, determine the rainwater runoff in each area of ​​the target building's roof. Step 230: Based on the rainwater runoff in each area of ​​the target building's roof, roof geometry, and gravity, determine the rainwater thickness and rainwater load distribution in the corresponding areas.

[0035] The following explains the specific implementation method for determining the wind-rain coupled two-phase flow wind field within the computational domain of the target building and its roof based on a 3D model and wind-rain coupling parameters.

[0036] First, the computational domain is defined based on the overall roof shape, slope distribution, and local structural features represented by the 3D model. These local structural features encompass the spatial location and geometric dimensions of complex structures such as gutters, drainage ditches, downspouts, parapets, ridges, eaves, and areas with openwork, multiple layers, or local protrusions or depressions. The computational domain refers to a specific spatial area defined for conducting numerical simulations of wind-rain coupled two-phase flow wind fields. Its boundaries must fully cover the target building's roof and surrounding areas affected by wind and rain to ensure that physical processes such as airflow and raindrop transport can be completely and realistically simulated, avoiding distortion of simulation results due to insufficient spatial range or improper boundary settings. Therefore, the computational domain is set with the core objective of ensuring the realism of the wind field simulation. The distance extending along the windward side of the target building's roof is no less than 5 times the building's maximum span, the distance extending along the leeward side is no less than 8 times the building's maximum span, and the distances extending on both sides are no less than 3 times the building's width. In the height direction, it covers the space from the ground to a point 5 times the maximum roof height above the highest point. This range avoids the computational domain boundary from intercepting or interfering with the airflow around the roof, ensuring that the flow characteristics of the wind field in the near-roof area are consistent with actual operating conditions. The shape of the computational domain is flexibly adjusted according to the surrounding terrain and spatial layout, typically using a cuboid or an irregular shape that conforms to the building's outline. The geometric boundaries conform to the roof surface outline, the main building facade, and the ground shape of the 3D model. For openwork structures, the boundary coordinates of the internal through-space are clearly defined to ensure that airflow can penetrate the openwork area. For multi-layered structures, the geometric boundaries of each layer and the gaps between layers are restored, so that the interaction between the wind field and each structure of the roof can be accurately captured.

[0037] Furthermore, the transport characteristics of the rainwater phase are determined based on the extreme rainfall parameters in the wind-rain coupling parameters. The extreme rainfall parameters include rainfall intensity, raindrop size distribution range, and raindrop terminal velocity under extreme meteorological conditions corresponding to the geographical area where the target building is located. The raindrop size distribution adopts a Marshall-Palmer distribution model that conforms to the rainfall characteristics of the region, covering a common size range from 0.5 mm to 5 mm. The terminal velocities corresponding to different sizes are calculated using a fitting formula based on measured rainfall data from the region. Specifically, the terminal velocity increases non-linearly with increasing droplet size: small-diameter raindrops (0.5 mm-1 mm) have a terminal velocity of 2 m / s-4 m / s, medium-diameter raindrops (1 mm-3 mm) have a terminal velocity of 4 m / s-7 m / s, and large-diameter raindrops (3 mm-5 mm) have a terminal velocity of 7 m / s-9 m / s. Based on these parameters, the mass concentration distribution benchmark of the rainwater phase is derived through the statistical distribution of rainfall intensity and raindrop size. Specifically, it is the total mass of raindrops of different sizes per unit volume, calculated using the formula: mass concentration = rainfall intensity / (raindrop terminal velocity × vertical projected area), with integral correction based on the raindrop size distribution. The kinematic viscosity coefficient of the rainwater phase is determined based on the raindrop size and the characteristics of the air medium in the region (such as the annual average air pressure and temperature), with a value ranging from 1.5 × 10⁻⁶. -5 m 2 / s to 2.0×10 -5 m 2 / s. The interphase force calculation model comprehensively considers the effects of air resistance, lift, gravity, and buoyancy on rainwater transport. Air resistance is calculated using either the Stokes drag formula or the Olsen drag formula, specifically selected based on the raindrop Reynolds number (the Stokes drag formula is used when the Reynolds number is ≤1, and the Olsen drag formula is used when 1 < Reynolds number ≤1000). Lift is derived based on the pressure difference generated by the airflow around the raindrops, ensuring that the transport behavior of the rainwater phase in the wind field is consistent with the actual movement law under extreme rainfall conditions in the area where the target building is located.

[0038] The flow boundary conditions for the air phase are set based on the extreme wind field parameters in the wind-rain coupling parameters. These parameters encompass the prevailing wind direction, average wind speed, and turbulence intensity, which are used to determine the velocity boundary conditions at the computational domain inlet. The inlet wind speed is set according to the average wind speed in the extreme wind field parameters, and the wind speed profile conforms to the logarithmic law distribution of the atmospheric boundary layer, meaning the wind speed increases logarithmically with height. The ground roughness is determined based on the topographic type of the building's location (e.g., urban built-up area, suburbs, open area), with a value ranging from 0.05m to 0.5m. The turbulence intensity is set based on measured data under preset extreme conditions. The turbulence intensity at the inlet varies with height, with 10%-15% near the ground and 5%-8% at roof height. The computational domain outlet uses a pressure outlet boundary condition, set to the local atmospheric pressure (101325 Pa), to ensure that the airflow can freely exit the computational domain without reflection interference. The target building's roof, main facade, and ground all employ no-slip boundary conditions. The surface roughness of the roof is consistent with the physical properties of the roof (such as material roughness) represented by the 3D model, simulating the adhesion and flow characteristics of air on a solid surface. Symmetrical boundary conditions are used at the top and sides of the computational domain, meaning the normal velocity and normal gradient of the airflow at the boundaries are zero, reducing additional interference from the boundaries on the wind flow and ensuring the independence of airflow motion within the computational domain.

[0039] After determining the computational domain, geometric boundaries, transport characteristics of the rainwater phase, and flow boundary conditions of the air phase, a two-phase flow numerical model of the air and rainwater phases was established based on the Euler two-fluid model principle, defining the coupling mechanism between the two phases. The air phase was treated as a continuous medium, and its flow characteristics were described by solving macroscopic governing equations. The rainwater phase was treated as a dispersed phase, distributed in the air phase as discrete particles, and the momentum and mass transfer coupling between the two phases was realized through an interphase force model. The entire system of complete and mutually coupled governing equations was constructed based on computational fluid dynamics theory.

[0040] The core governing equations for the air phase include the continuity equation and the Reynolds-averaged Navier-Stokes equations. The continuity equation follows mass conservation and is expressed as follows: + (ρ a a )=0, where ρ a Let be the air density, and t be the time. a The air phase velocity vector, The Hamiltonian operator is used to characterize spatial gradient changes. This equation intuitively reflects the variation of air density with time and space, ensuring the conservation of air mass within the computational domain. The Reynolds-averaged Navier-Stokes equations ensure momentum conservation and account for the effects of turbulent fluctuations; the expression is as follows: + (ρ a a a )=- p+ (μ a ( a + a T ))+ (-ρ a )+ρ a +S ap In each parameter, p represents the static pressure of the air phase, and μ represents the static pressure of the air phase. a Aerodynamic viscosity, Let Reynolds stress tensor be the stress tensor. S is the gravitational acceleration vector. ap The momentum exchange source term between the air phase and the rainwater phase is used to reflect the drag effect of raindrop particles on the airflow. The left side of the equation characterizes the rate of change of air phase momentum with time and the convective transport term. The right side corresponds to the pressure gradient force, viscous stress, turbulent stress, gravity and interphase forces, respectively, comprehensively describing the force and motion equilibrium relationship of the air phase. The flow field distribution of the air phase can be obtained by coupling the two types of equations.

[0041] The rainwater phase control equations employ the transport equations of a discrete phase model, using individual raindrop particles as the computational unit, and derive the motion equations based on Newton's second law. = ,in p Let m be the velocity vector of the raindrop particles. p The mass of the particle is determined by the particle volume and the density ρ of the rainwater. p (1000kg / m 3 The calculation yields m. p =(4 / 3)πr p 3 ρ p (r) p (Raindroplet diameter). For air resistance, according to the Reynolds number Re p = / (d p =2r p Choose the corresponding formula for the particle diameter, when Re p When ≤1, use the Stokes resistance formula. =3πμ a d p ( When 1 <Re pWhen the value is ≤1000, the Ossen resistance formula is used. =3πμ a d p ( (1+) ). For lift, it is derived based on the airflow around the source as follows: =0.5C L ρ a πr p 2 | | 2 L C L The lift coefficient (0.05~0.1 for spherical raindrops) is used. L It is the unit vector of the lift direction (perpendicular to the direction of the particle's relative velocity). For gravity, the expression is: =m p . Buoyancy is the force that acts in the opposite direction to gravity, and its expression is: =(4 / 3)πr p 3 ρ a This equation fully describes the acceleration change of raindrop particles in a wind field, and the velocity and displacement trajectory of the particles can be further obtained by integration.

[0042] The k-ε two-equation model was specifically chosen for the turbulence model. This model exhibits good stability and engineering applicability in high Reynolds number flows, flows around bluff bodies in structures, and separated flows. The expression for the turbulent kinetic energy k-equation is as follows: + (ρ a a k)= [(μ a +μ t / σ k ) k]+G k -ρ a The equation for ε, the turbulent dissipation rate ε, is as follows: + (ρ a a ε)= [(μ a +μ t / σ ε ) ε]+C1ε(ε / k)G k -C2ερa ε 2 / k, where k is the turbulent kinetic energy, ε is the turbulent dissipation rate, and μ t =ρ a C μ k 2 / ε is the turbulent viscosity, σ k =1.0、σ ε =1.3 is the Prandtl number for turbulence, G k =-ρ a ∇ a For the turbulent kinetic energy generation term (related to the velocity gradient), the model constants adopt the engineering standard value C. μ =0.09, C1ε=1.44, C2ε=1.92. Solving the two equations together can accurately capture turbulent characteristics such as airflow separation and recirculation around the roof.

[0043] Furthermore, the finite volume method is used to discretize the governing equations. First, the computational domain is divided into a hybrid structured or unstructured mesh matching the scale of the roof's discrete mesh. Hexahedral structured meshes with side lengths of 0.5m~1.0m are used in areas with simple roof structures (such as smooth slopes), while tetrahedral unstructured meshes with side lengths refined to 0.05m~0.1m are used in densely constructed areas such as gutters and downspouts. Simultaneously, the mesh quality verification standards are met: twist ≤ 0.8, aspect ratio ≤ 5, orthogonality ≥ 0.3, to avoid numerical oscillations caused by poor mesh quality. For spatial discretization, the convection term adopts a second-order upwind scheme, expressed as follows: (f is the mesh surface, S) f The area vector of the grid surface. For general variables such as velocity, k, and ε, the computational accuracy is improved by introducing the physical quantity gradients of adjacent grids. The diffusion term uses a central difference scheme to ensure numerical stability. The time discretization uses an implicit Euler scheme to discretize the time derivative term into... (Δt is the time step, ranging from 0.001s to 0.01s). It is more adaptable to the time step, and the computational efficiency can be improved by increasing the time step, while ensuring the iterative stability under complex flow fields.

[0044] A dual convergence criterion is set during the iterative solution process to ensure computational accuracy. The first criterion is the residual convergence criterion, requiring the residuals of the mass conservation equation, momentum conservation equation, and turbulence equations (k-equation, ε-equation) to be less than 1e-4. This threshold is a commonly used accuracy standard in building wind field simulation and can effectively control numerical errors. The second criterion is the physical quantity stability criterion, which monitors the pressure coefficient and wind speed distribution in key areas of the roof (such as the ridge, eaves, and gutter area) in real time. When the change in the above physical quantities is less than 1% in 500 consecutive iterations, the flow field calculation is considered to have reached a stable convergence state, avoiding result distortion due to insufficient iteration. Through the coupled solution of the control equations using the above process, the wind-rain coupled two-phase flow wind field within the computational domain of the target building and roof is finally obtained. This wind field result can completely output the core physical parameters at different spatial locations. The air phase includes the velocity vector (including magnitude and direction), static and dynamic pressure distribution, and turbulence intensity; the rainwater phase includes the mass concentration distribution (total mass of raindrops per unit volume) and the raindrop velocity vector (including deflection velocity after the wind field).

[0045] The following explains the specific implementation method of determining the trajectory of raindrop particles based on the wind-rain coupling two-phase flow wind field, and determining the rainwater runoff in each area of ​​the target building roof based on the trajectory.

[0046] Based on the obtained wind-rain coupled two-phase flow field, the Lagrange method is used to calculate and analyze the trajectory of raindrop particles. First, considering the wind field coverage, the horizontal projection size of the roof, and the comprehensive requirements of rainfall simulation, the seeding area and seeding intensity of raindrop particles are delineated. The seeding area is based on the top of the computational domain, extending laterally beyond the horizontal projection range of the roof by no less than twice the maximum span of the roof, and longitudinally covering the entire space from the top of the computational domain to the highest point of the roof, ensuring that particle seeding can cover all potentially rain-affected areas of the roof and the surrounding airflow. The seeding intensity is precisely calculated using extreme rainfall parameters such as rainfall intensity, raindrop size distribution, and computational domain height. Specifically, based on the raindrop flux per unit area per unit time, the seeding quantity of different particle sizes is allocated according to the proportion of raindrop size distribution, so that the total mass of seeds seeded per unit time is consistent with the rainfall mass per unit area under actual extreme rainfall conditions. The seeding quantity ratio of small-diameter raindrops (0.5mm-1mm), medium-diameter raindrops (1mm-3mm), and large-diameter raindrops (3mm-5mm) perfectly matches the particle size ratio in the Marshall-Palmer distribution model.

[0047] Based on the seeding area and intensity, discrete raindrop particles are uniformly released within the computational domain. The initial physical parameters of the particles are matched to extreme rainfall parameters, and the initial terminal velocities of particles of different sizes are assigned according to corresponding intervals. Simultaneously, the initial positions of the particles are randomly distributed within the seeding area to avoid trajectory statistical deviations caused by concentrated release. After seeding, the motion parameters of the raindrop particles are derived by combining the air phase flow parameters (such as wind speed vectors, turbulence intensity, and pressure distribution at various spatial points) and the rainwater phase transport characteristics (such as interphase force models and kinematic viscosity coefficients) in the wind-rain coupled two-phase flow field.

[0048] The particle's force state integrates air resistance, lift, gravity, and buoyancy; the calculation logic and parameter definitions for each force are clearly quantified. Air resistance is based on the raindrop Reynolds number Re. p Calculate, the expression is According to Re p Choose the corresponding formula for the range of values ​​of Re. p When ≤1, the Stokes resistance formula is used. , when 1<Re p When the value is ≤1000, the Olsen resistance formula is used. Ensure that the direction of drag is strictly opposite to the direction of relative motion. Lift is derived based on the pressure difference generated by airflow around raindrops, using the formula... Gravity press Calculation. Buoyancy and gravity act in opposite directions; the expression is: This perfectly conforms to Archimedes' principle. The net force acting on the particle is a sum of four force vectors, F. total =F D +F L +F G +F B Based on Newton's second law, the acceleration a = F can be directly derived. total / m p The acceleration vector accurately reflects the changing trend of a particle's motion state. The rate of change of velocity is obtained by integrating the acceleration over time, specifically using a definite integral form. This integration method accurately yields the particle velocity at any given moment, fully characterizing the dynamic change of particle velocity over time. Based on the aforementioned motion parameters (net force, acceleration, initial velocity), the fourth-order Runge-Kutta (RK4) numerical integration method is used to solve the particle's equation of motion. The integration step size is set to 0.001 s. During the integration process, the particle position at time t is set to (x... n ,y n ,z n ), speed is (u n ,v n ,w n First, calculate the four intermediate increments k1, k2, k3, and k4, which contain both position and velocity increments. The velocity increments satisfy k1u =a x (t,x n ,y n ,z n ,u n ,v n ,w n )•Δt,k1 v =a y (t,x n ,y n ,z n ,u n ,v n ,w n )•Δt,k1 z =a z (t,x n ,y n ,z n ,u n ,v n ,w n ))•Δt, the position increment satisfies k1 x =u n •Δt,k1 y =v n •Δt,k1 z =w n •Δt, subsequent intermediate increments k2, k3, and k4 are derived according to the RK4 standard formula, and the final position (x) at time t+Δt. n+1 ,y n+1 ,z n+1 ) and velocity (u n+1 ,v n+1 ,w n+1 The weighted average of each increment ensures the accuracy of the iterative calculation.

[0049] Through the complete iterative process described above, the complete spatial trajectory of each raindrop particle under the influence of the wind field is finally obtained. The trajectory data is stored in an ordered time series, and each integration step includes three-dimensional coordinates (specific values ​​of the X, Y, and Z axes), velocity vectors (u, v, and w components), and motion direction angles (azimuth and elevation). By comparing the trajectory data under windless and wind-coupled conditions, the deflection effect of the wind field on the raindrop's motion path can be clearly shown. For example, the prevailing wind will cause the raindrop trajectory to shift towards the leeward side, and the turbulence intensity will cause small random fluctuations in the trajectory. These characteristics are all intuitively reflected through the quantitative differences in the trajectory data.

[0050] During trajectory tracking, it is determined in real time whether particles come into contact with the geometric boundary of the target building's roof. Contact determination is based on whether the shortest distance between the particle's center coordinates and the roof's 3D model surface coordinates is less than a set threshold (0.001m). This threshold is determined based on the minimum side length of the roof's discrete mesh, ensuring that no particles that are actually in contact are missed, nor are particles that are not in contact at close range mistakenly identified as being in contact. Once a particle is determined to be in contact with the roof, it is transformed into a runoff unit moving along the roof surface. The runoff unit is a discretized representation of the roof rainwater runoff formed after contact with the roof. Its mass and volume are completely consistent with the original raindrop particle, and it inherits the component of the particle's velocity along the tangent direction of the roof when it contacts the roof, while the velocity component perpendicular to the roof normal direction is completely lost due to contact collision. Combining the physical characteristics of the target building's roof (such as the friction coefficient corresponding to surface roughness and material permeability coefficient) and the slope distribution and structural features in the 3D model, the motion path of the runoff unit is derived. The runoff units always move along the direction of the gravitational potential energy gradient of the roof at their location (i.e., the direction of the steepest slope). The acceleration is calculated from the difference between the component of gravity along the slope and the frictional force. The frictional force is calculated as the product of the friction coefficient and the normal pressure exerted by the runoff unit on the roof. When encountering structures such as gutters or drainage ditches, the direction of movement is adjusted according to the geometric boundaries of the structure, continuing to move along the extension direction of the structure or the drainage slope direction. When encountering obstructing structures such as parapet walls, if the kinetic energy is insufficient to overcome the obstruction, the flow turns along the edge of the structure; if the kinetic energy is sufficient, it crosses the structure and enters the adjacent area. The runoff units flowing across zones continuously record the zone number and grid information they pass through, ensuring that the path fully reflects the comprehensive influence of the roof's geometry, physical properties, and structural constraints.

[0051] Furthermore, using the roof's discrete grid as the statistical unit, and combining the movement path of the runoff units with the structural boundaries and functional zoning results of the roof, the cross-regional flow trajectories that cross structural boundaries or functional zones during the movement of runoff units are identified. Based on the zoning relationship of the roof's discrete grid, an association mapping is established between the cross-regional flow trajectories and the upstream starting and downstream terminating discrete grids, ensuring the traceability of the source and destination of cross-regional runoff. Through the association of grid attributes in the 3D model, all grid IDs passed through by each runoff unit are recorded. The number of original runoff unit trajectories formed by raindrop particles directly contacting the roof within each discrete grid, as well as the number of cross-regional runoff unit trajectories merged through the association mapping, are counted. Then, combined with the actual area of ​​the corresponding discrete grid, the trajectory density of each grid (the ratio of the total number of trajectories to the grid area) is calculated. During the continuous increase of raindrop particle quantity, the change in trajectory density of each grid is monitored in real time. Each increase involves 20% of the initial seeding amount. After each round of increases, the trajectory density of each grid is recalculated. When the rate of change in trajectory density of all grids is less than 3% after three consecutive increases, the trajectory density is considered to have reached a statistically stable state. At this point, the trajectory density objectively reflects the probability of rainfall and runoff collection characteristics in each area of ​​the roof, avoiding fluctuations in results due to insufficient particle quantity. Based on the stabilized trajectory density, the rainwater runoff in each area of ​​the target building's roof is calculated by combining the correlation between extreme rainfall parameters and raindrop particle seeding intensity. The seeding intensity conversion coefficient K is determined by the ratio of the actual rainfall intensity I to the number of particles seeded per unit area N per unit time (K=I / N). The rainwater runoff in each area of ​​the target building's roof is then calculated using the formula (rainwater runoff = trajectory density × seeding intensity conversion coefficient × rainwater density × grid area), with the rainwater density taken as 1000 kg / m². 3 This ensures that the calculated flow rate is consistent with the actual roof drainage capacity under extreme rainfall conditions. At the same time, the drainage flow rate of each grid is associated with its respective zone to form zone drainage flow statistics.

[0052] After obtaining the rainwater runoff in each area of ​​the roof, the rainwater thickness in the corresponding area is calculated by combining the runoff width and slope parameters in the roof geometry. The runoff width is determined based on the slope aspect and structural distribution of the roof area where each grid is located. For flat slope areas, the runoff width is taken as the effective width of the area perpendicular to the runoff direction, calculated using the grid coordinate range. For linear structural areas such as gutters and drainage ditches, the runoff width is taken as the actual cross-sectional width of the structure. The slope parameter uses the actual roof slope value associated with each grid, calculated using the elevation data of the 3D model. The rainwater thickness is calculated using the formula (rainwater thickness = rainwater runoff / (runoff width × basic runoff velocity)), where the basic runoff velocity v is derived based on the roof slope and gravitational acceleration; the specific formula is v = g is taken as 9.8 m / s 2L represents the path length of the runoff element within the grid, and θ is the roof slope angle, ensuring that the rainwater thickness reflects the constraint effect of roof geometry on rainwater flow. Based on this, and considering rainwater density (1000 kg / m³),... 3 ) and gravitational acceleration (9.8 m / s²) 2 The roof rainwater load for each discrete grid is calculated using the formula (rainwater load = rainwater thickness × rainwater density × gravitational acceleration × grid projected area). The grid projected area is the area projected onto the horizontal plane, calculated using the grid's X and Y axis coordinates and slope. Finally, based on the location coordinates, zone, and corresponding rainwater load value of each grid, a rainwater load distribution map of the target building's roof is formed, clearly showing the differences in rainwater load in different areas and structures of the roof.

[0053] The following explains the specific implementation method for determining the rainwater runoff thickness and rainwater load distribution in each area of ​​the target building's roof based on the rainwater runoff, roof geometry, and gravity.

[0054] The calculation of rainwater runoff thickness is based on the rainwater runoff in each area, combined with the runoff width and slope parameters in the roof geometry, and also incorporates the constraint effect of the roof's physical characteristics on rainwater flow. The determination of runoff width is adapted to different roof structures and slope characteristics. For areas with flat slopes and uniform slope aspect, the effective width perpendicular to the runoff direction is calculated, derived from the coordinate range of the roof's discrete grid and slope aspect data, specifically based on the projected length of the grid boundary in the direction perpendicular to the runoff path. For linear drainage structures such as gutters and drainage ditches, their actual cross-sectional width is directly used. This width is taken from the design dimensions of the structure in the roof's 3D model to ensure direct matching with the structure's drainage capacity. For complex areas with multiple slope aspects and significant undulations, multiple sub-runoff zones are divided based on the movement path of the runoff units. The effective width of each sub-runoff zone is calculated independently according to the discrete grid range it covers, and then integrated by weighted average to obtain the comprehensive runoff width of the area. The weighting coefficient is the proportion of the runoff in each sub-runoff zone. The slope parameters directly adopt the actual slope values ​​associated with each grid in the 3D roof model, fully considering details such as local slope changes and slope transitions. For areas with abrupt slope changes, the instantaneous slope value along the runoff unit's path is used as the calculation basis to ensure that the influence of gravity on rainflow is accurately depicted. Rainflow thickness is calculated through the correlation between catchment flow and runoff width, and refined runoff velocity. The refined runoff velocity is derived based on the component of gravity along the slope and roof friction resistance, with the formula v= In the formula, μ is the friction coefficient of the roof surface (the value is taken according to the characteristics of the roof material, such as 0.01~0.03 for concrete roofs and 0.005~0.015 for metal roofs), and λ is the runoff correction coefficient (the value is taken as 0.05~0.1 in combination with the roof roughness and the influence of local structures). It comprehensively reflects the influence of slope, friction resistance and structural constraints on runoff velocity, so that the rain flow thickness can truly reflect the thickness difference of rainwater flow in different areas, and adapt to the runoff characteristics of large-span and complex geometric roofs.

[0055] Rainwater load calculation is based on rainwater thickness, combined with rainwater density, gravitational acceleration, and the quantification of the projected area of ​​the roof's discrete grid. The calculation logic is optimized for complex roof structures. The grid projected area is the size of the discrete grid projected onto the horizontal plane. Specifically, for planar grids, the horizontal projected area is calculated directly from the grid's X and Y axis coordinate range. For curved or inclined grids, it is obtained by multiplying the actual area of ​​the grid by the cosine of the roof slope angle, i.e., Aprojected = Aactual × cosθ (where θ is the roof slope angle of the area where the grid is located). For complex structural areas such as openwork or multi-layered structures, the grid projected area of ​​the openwork portion is calculated based on the actual connected area; for multi-layered areas, the projected area of ​​each independent grid layer is calculated separately, and then integrated into a total load based on the inter-layer force transfer relationship. After calculating the rainwater load for each discrete grid according to the above parameters, and combining the zoning and structural features of the roof 3D model, a rainwater load distribution map of the target building roof is formed. The map clearly marks the load value, zone, and corresponding structural type of each grid, and also associates the key parameters of the wind-rain coupling condition (such as rainfall intensity and wind speed) corresponding to each load value. This distribution map can clearly present the load differences in different areas and structures (such as the edges of openwork areas, the junctions of multi-layered structures, and the intersections of gutters), reflecting the non-uniform distribution characteristics of roof rainwater load under wind-rain coupling.

[0056] Step 130: Based on the rainwater runoff, rainwater thickness and rainwater load distribution of each area of ​​the target building roof under multiple wind and rain coupling conditions, determine the envelope extreme value of the rainwater effect on the target building roof.

[0057] First, combining the wind rose diagram of the target building's location, measured extreme weather data (including wind speed and rainfall intensity statistics) from meteorological departments for different return periods, and the core requirements of engineering design limit verification, a multi-set wind-rain coupling condition matrix covering all potentially adverse scenarios is constructed. The matrix encompasses wind direction, wind speed, and extreme rainfall intensity. Wind direction is divided into eight main directions: east, south, west, north, northeast, southeast, northwest, and southwest, further subdivided into 16 secondary directions (such as 30° east of northeast, 45° south of southwest, etc.), comprehensively covering the dominant wind directions in the region and unfavorable oblique winds that may cause localized water accumulation on roofs. Three wind speed levels are selected, corresponding to the 50-year, 100-year, and 200-year return period extreme wind speeds for the region. The values ​​are directly taken from the maximum values ​​of the corresponding return periods measured and statistically analyzed by meteorological departments over the past 30 years, with minor adjustments made based on the airflow characteristics of the building's location (plains, hills, mountains) to ensure a close match to the actual effects of extreme wind fields. Extreme rainfall intensity is combined with two types of values: one is the once-in-a-century extreme rainfall intensity in the region (taken from the statistics of continuous measured rainfall intensity peaks by the meteorological department), and the other is the rainfall intensity threshold corresponding to the ultimate design of the drainage system in engineering practice. The two types of rainfall intensity are combined with all wind directions and wind speeds to form no less than 24 independent wind and rain coupling conditions, which fully cover all kinds of adverse situations that the roof may face under the combined action of wind and rain.

[0058] For each wind-rain coupling scenario, the entire process of independent calculation—including wind field calculation, raindrop particle trajectory tracking, roof rainwater runoff derivation / rainflow thickness and rainwater load calculation—is followed in step 120. The calculation parameters (computation domain boundary range, particle seeding intensity, trajectory stability criterion, convergence standard, etc.) for each scenario remain completely consistent to ensure horizontal comparability of calculation results under different scenarios. The calculation results for all scenarios are stored uniformly in a structured format, using the roof discrete grid as the smallest data unit. Each data entry is associated with the grid ID, its partition number, a unique scenario identifier (including wind direction angle, wind speed value, and rainfall intensity value), specific values ​​for rainwater runoff, rainflow thickness, and rainwater load. It also includes a trajectory density stability determination record (total particle seeding amount at stability, density change rate after three consecutive particle increments) and calculation convergence information (residual convergence value, iteration steps), forming a traceable and verifiable multi-scenario result database.

[0059] After completing calculations for all preset working conditions, envelope extreme value statistical analysis is conducted based on the constructed multi-working-condition result database, following a progressive logic of grid level and zone level. Grid-level statistics take a single discrete grid as the object, and by traversing the rainwater runoff, rainwater thickness, and rainwater load data of the grid under all 24 working conditions, the maximum value of each parameter group is selected as the three envelope extreme values ​​of the grid. At the same time, the unique identifier of the working condition and key parameters (the specific wind direction, wind speed, and rainfall intensity that caused the extreme value) corresponding to each extreme value are recorded to identify the most unfavorable wind and rain coupling conditions of the grid. Zonal-level statistics are based on pre-defined zoning of the 3D model (divided by roof slope, structural type, or functional area). The three envelope extreme values ​​of all grids within the same zoning are summarized, and the maximum envelope extreme value, average envelope extreme value, and standard deviation of the extreme values ​​are calculated. The maximum envelope extreme value reflects the most unfavorable stress point within the zoning, the average envelope extreme value reflects the overall stress level of the zoning, and the standard deviation quantifies the degree of stress difference within the zoning. Simultaneously, the working condition information corresponding to all extreme values ​​within the zoning is integrated to identify the dominant wind direction and speed combination that has the most adverse impact on the zoning, with particular attention paid to the extreme value distribution characteristics in areas with concentrated cross-regional flow runoff units. Through progressive statistics at the grid and zoning levels, the final results are the extreme values ​​of rainwater runoff envelope, rainwater thickness envelope, and rainwater load envelope for each grid and zoning of the target building's roof, comprehensively covering the most unfavorable rainwater action state of the roof under all extreme wind and rain coupling conditions.

[0060] Step 140: Analyze the rainwater runoff characteristics and rainwater load of the target building roof based on the envelope extreme values.

[0061] After obtaining the envelope extreme values ​​of rainwater runoff, rainwater thickness, and rainwater load on the target building roof through progressive statistics at the grid and zone levels, the system conducts analysis of roof rainwater runoff characteristics and rainwater load based on data from these extreme wind and rain coupling conditions. By comparing the numerical differences and spatial distribution of envelope extreme values ​​in different zones, key catchment areas with significantly higher runoff and rainwater thickness are identified, and the correlation between these areas and roof structure is analyzed. For example, whether gutter junctions, the area around downspouts, areas with abrupt slope changes, or areas with concentrated cross-zone flow are the core of the runoff is investigated. At the same time, the runoff composition of key catchment areas is traced, the contribution ratio of primary runoff and cross-zone inflow runoff is distinguished, the degree of matching between the runoff path and the direction of roof gravitational potential energy gradient and structural boundary constraints is verified, and the risk of runoff congestion or stagnation due to local structural obstruction or unreasonable slope design is determined.

[0062] Based on the extreme values ​​of rainwater load envelope, and in accordance with the load limit standards in the building structural design code, a safety check of the roof structure was conducted. The extreme values ​​of the maximum rainwater load envelope in each zone were quantitatively compared with the structural design bearing capacity of the corresponding area. Attention was paid to the load-bearing capacity of key catchment areas and weak roof structures (such as the edges of openwork areas, the junctions of multi-layered structures, and the middle sections of large-span slopes). The impact of uneven load distribution on structural stress was analyzed, identifying risk points of local load exceeding limits or stress concentration. Simultaneously, by combining the most unfavorable wind and rain conditions parameters corresponding to the extreme values ​​of the envelope (such as the combination of prevailing wind direction, wind speed, and rainfall intensity), the weak points of the structure under extreme weather conditions were identified, providing a basis for structural reinforcement or structural optimization.

[0063] It is understood that, in order to achieve the functions in the above embodiments, the computer device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and method steps described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0064] Furthermore, as a response to the above Figure 1 The implementation of the method embodiment shown in this application provides a building roof rainwater analysis device. This device embodiment corresponds to the foregoing method embodiments. For ease of reading, this embodiment will not repeat the details of the foregoing method embodiments one by one, but it should be clear that the device in this embodiment can correspondingly implement all the contents of the foregoing method embodiments. Specifically, as shown... Figure 3 As shown, the building roof rainwater analysis device 300 includes:

[0065] Model building module 310 is used to build a three-dimensional model of the target building's roof.

[0066] The first determining module 320 is used to determine the rainwater runoff, rainwater thickness and rainwater load distribution of each area of ​​the target building roof under multiple wind and rain coupling conditions based on the three-dimensional model, multiple sets of wind and rain coupling parameters, the interaction characteristics between raindrop particles and the target building roof, and the physical characteristics of the target building roof.

[0067] The second determining module 330 is used to determine the envelope extreme value of the rainwater effect on the roof of the target building based on the rainwater runoff, rainwater thickness and rainwater load distribution in each area of ​​the roof of the target building under multiple sets of wind and rain coupling conditions.

[0068] Analysis module 340 is used to analyze the rainwater runoff characteristics and rainwater load of the target building roof based on the envelope extreme value.

[0069] Furthermore, such as Figure 3 As shown, the first determining module 320 is specifically used to determine the wind-rain coupled two-phase flow wind field in the computational domain of the target building and roof based on the three-dimensional model and wind-rain coupling parameters; determine the motion trajectory of raindrop particles based on the wind-rain coupled two-phase flow wind field; determine the rainwater runoff in each area of ​​the target building roof based on the motion trajectory; and determine the rainwater runoff thickness and rainwater load distribution in the corresponding area based on the rainwater runoff in each area of ​​the target building roof, roof geometry, and gravity.

[0070] Furthermore, such as Figure 3 As shown, the first determining module 320 is specifically used to determine the computational domain range and geometric boundary of the wind-rain coupled two-phase flow wind field based on the overall roof shape, slope distribution and local structural features represented by the three-dimensional model; to determine the transport characteristics of the rainwater phase based on the extreme rainfall parameters in the wind-rain coupling parameters; to determine the flow boundary conditions of the air phase based on the extreme wind field parameters in the wind-rain coupling parameters; and to determine the wind-rain coupled two-phase flow wind field within the computational domain of the target building and roof based on the computational domain range, geometric boundary, rainwater phase transport characteristics and air phase flow boundary conditions.

[0071] Furthermore, such as Figure 3 As shown, the first determining module 320 is specifically used to determine the seeding area and seeding intensity of raindrop particles based on the coverage of the wind-rain coupled two-phase flow wind field and the preset rainfall simulation requirements; release discrete raindrop particles based on the seeding area and seeding intensity; determine the motion parameters of raindrop particles based on the air phase flow boundary conditions and rainwater phase transport characteristics in the wind-rain coupled two-phase flow wind field; and determine the motion trajectory of raindrop particles under the action of the wind field based on the motion parameters.

[0072] Furthermore, such as Figure 3 As shown, the first determining module 320 is specifically used to: determine the raindrop particles that come into contact with the roof of the target building based on the movement trajectory of the raindrop particles and the geometric boundary of the roof of the target building; convert the raindrop particles in contact with the roof into runoff units moving along the roof surface; determine the movement path of the runoff units along the direction of the gravitational potential energy gradient of the roof based on the physical characteristics of the roof of the target building; determine the trajectory density of the runoff units in each discrete grid based on the movement path and the area of ​​the discrete grid of the roof of the target building; determine whether the trajectory density has reached stability based on the change of trajectory density during the continuous increase of the number of raindrop particles; and determine the rainwater runoff in each area of ​​the roof of the target building based on the correlation between the stable trajectory density, extreme rainfall parameters and raindrop particle dispersal intensity.

[0073] Furthermore, such as Figure 3As shown, the first determining module 320 is specifically used to determine the cross-regional flow trajectory of the runoff unit during its movement by crossing the structural boundary or functional zone based on the movement path and the structural boundary and functional zoning results of the target building roof; to establish the association mapping between the cross-regional flow trajectory and the upstream starting discrete grid and the downstream ending discrete grid based on the zoning relationship of the discrete grid of the target building roof; to count the number of original runoff unit trajectories formed by the transformation of raindrop particles directly contacting the roof in each discrete grid, and the number of cross-regional runoff unit trajectories merged in through the association mapping; and to determine the trajectory density of runoff units in each discrete grid by combining the number of original runoff unit trajectories, the number of cross-regional runoff unit trajectories and the area of ​​the corresponding discrete grid.

[0074] Furthermore, such as Figure 3 As shown, the first determining module 320 is specifically used to determine the rainwater runoff thickness of each area of ​​the target building roof based on the rainwater runoff flow rate of each area, the roof runoff width and slope conditions of the corresponding area; based on the rainwater runoff thickness, rainwater density and gravitational acceleration, combined with the projected area of ​​the discrete grid of the roof of each area, to determine the roof rainwater load of the corresponding area; and to form the rainwater load distribution of the target building roof according to the roof rainwater load of each area.

[0075] Optionally, the building roof rainwater analysis device may be an electronic device with data processing capabilities, or a functional module within the electronic device, without limitation.

[0076] For example, the electronic device can be a server, which can be a single server or a server cluster consisting of multiple servers. As another example, the electronic device can be a mobile phone, tablet computer, desktop computer, laptop computer, handheld computer, notebook computer, ultra-mobile personal computer (UMPC), netbook, as well as cellular phones, personal digital assistants (PDAs), augmented reality (AR) devices, virtual reality (VR) devices, and other terminal devices. As yet another example, the electronic device can also be a recording device, video surveillance equipment, etc. This application does not impose any special limitations on the specific form of the electronic device.

[0077] The following example uses an electronic device for analyzing rainwater from building roofs. Figure 4 As shown, Figure 4 The hardware structure of an electronic device 400 provided in this application.

[0078] like Figure 4 As shown, the electronic device 400 includes a processor 410, a communication line 420, and a communication interface 430.

[0079] Optionally, the electronic device 400 may also include a memory 440. The processor 410, memory 440, and communication interface 430 can be connected via a communication line 420.

[0080] The processor 410 can be a central processing unit (CPU), a general-purpose processor, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof. The processor 410 can also be any other device with processing capabilities, such as a circuit, device, or software module, without limitation.

[0081] In one example, processor 410 may include one or more CPUs, for example Figure 4 CPU0 and CPU1 in the CPU.

[0082] As an optional implementation, electronic device 400 may include multiple processors, for example, in addition to processor 410, it may also include processor 470. Communication line 420 is used to transmit information between the components included in electronic device 400.

[0083] Communication interface 430 is used for communicating with other devices or other communication networks. These other communication networks can be Ethernet, Radio Access Network (RAN), Wireless Local Area Networks (WLAN), etc. Communication interface 430 can be a module, circuit, transceiver, or any device capable of enabling communication.

[0084] Memory 440 is used to store instructions. These instructions can be computer programs.

[0085] The memory 440 can be a read-only memory (ROM) or other type of static storage device that can store static information and / or instructions; it can also be a random access memory (RAM) or other type of dynamic storage device that can store information and / or instructions; it can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, etc., without limitation.

[0086] It should be noted that the memory 440 can exist independently of the processor 410, or it can be integrated with the processor 410. The memory 440 can be used to store instructions, program code, or some data, etc. The memory 440 can be located inside or outside the electronic device 400, without restriction.

[0087] The processor 410 is configured to execute instructions stored in the memory 440 to implement the communication method provided in the following embodiments of this application. For example, when the electronic device 400 is a terminal or a chip in a terminal, the processor 410 can execute instructions stored in the memory 440 to implement the steps performed by the transmitting end in the following embodiments of this application.

[0088] As an optional implementation, the electronic device 400 also includes an output device 450 and an input device 460. The output device 450 can be a display screen, speaker, or other device capable of outputting data from the electronic device 400 to the user. The input device 460 can be a keyboard, mouse, microphone, joystick, or other device capable of inputting data into the electronic device 400.

[0089] It should be pointed out that, Figure 4 The structure shown does not constitute a limitation on the electronic device, except... Figure 4 In addition to the components shown, the electronic device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0090] The building roof rainwater analysis device and application scenarios described in this application are for the purpose of more clearly illustrating the technical solutions of this application, and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the evolution of building roof rainwater analysis devices and the emergence of new business scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0091] This application provides a storage medium storing a program that, when executed by a processor, implements the building roof rainwater analysis method.

[0092] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0093] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0094] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for analyzing rainwater from building roofs, characterized in that, The method includes: Create a 3D model of the target building's roof; Based on the three-dimensional model, multiple sets of wind and rain coupling parameters, the interaction characteristics between raindrop particles and the roof of the target building, and the physical characteristics of the roof of the target building, the rainwater runoff, rainwater thickness, and rainwater load distribution of each area of ​​the roof of the target building under multiple sets of wind and rain coupling conditions are determined respectively. The multiple sets of wind and rain coupling conditions cover the combination scenarios of unfavorable wind direction, extreme wind speed, and extreme rainfall at different return periods in the area where the target building is located, and the parameter values ​​of the wind and rain coupling parameters corresponding to each set of wind and rain coupling conditions are different. Based on the rainwater runoff, rainwater thickness, and rainwater load distribution in each area of ​​the target building roof under the multiple sets of wind and rain coupling conditions, the envelope extreme value of the rainwater effect on the target building roof is determined. The rainwater runoff characteristics and rainwater load of the target building roof are analyzed based on the envelope extreme values. Based on the aforementioned 3D model, multiple sets of wind-rain coupling parameters, the interaction characteristics between raindrop particles and the target building roof, and the physical characteristics of the target building roof, the rainwater runoff, rainwater thickness, and rainwater load distribution in each area of ​​the target building roof under multiple wind-rain coupling conditions are determined, including: Based on the three-dimensional model and the wind-rain coupling parameters, the wind-rain coupling two-phase flow field within the computational domain of the target building and its roof is determined; Based on the wind-rain coupled two-phase flow field, the trajectory of raindrop particles is determined, and the rainwater runoff in each area of ​​the target building roof is determined based on the trajectory. Based on the rainwater runoff, roof geometry, and gravity in each area of ​​the target building's roof, the rainwater thickness and rainwater load distribution in the corresponding areas are determined.

2. The method according to claim 1, characterized in that, Based on the three-dimensional model and the wind-rain coupling parameters, the wind-rain coupling two-phase flow field within the computational domain of the target building and its roof is determined, including: Based on the overall roof shape, slope distribution and local structural features represented by the three-dimensional model, the computational domain and geometric boundary of the wind-rain coupled two-phase flow field are determined. Based on the extreme rainfall parameters in the wind-rain coupling parameters, the transport characteristics of the rainwater phase are determined. Based on the extreme wind field parameters in the wind-rain coupling parameters, the flow boundary conditions of the air phase are determined; Based on the computational domain range, the geometric boundary, the rainwater phase transport characteristics, and the air phase flow boundary conditions, the wind-rain coupled two-phase flow wind field within the computational domain where the target building and roof are located is determined.

3. The method according to claim 2, characterized in that, Determining the trajectory of raindrop particles based on the wind-rain coupled two-phase flow field includes: Based on the coverage of the wind-rain coupled two-phase flow wind field and the preset rainfall simulation requirements, the seeding area and seeding intensity of raindrop particles are determined. Discrete raindrop particles are released based on the dispersing area and the dispersing intensity; Based on the air phase flow boundary conditions and rainwater phase transport characteristics in the wind-rain coupled two-phase flow field, the motion parameters of the raindrop particles are determined. The trajectory of the raindrop particles under the influence of the wind field is determined based on the motion parameters.

4. The method according to claim 3, characterized in that, Determining the rainwater runoff in each area of ​​the target building's roof based on the motion trajectory includes: Based on the trajectory of the raindrop particles and the geometric boundary of the target building roof, the raindrop particles that come into contact with the target building roof are determined. The raindrop particles that come into contact with the roof are converted into runoff units that move along the roof surface; Based on the physical characteristics of the target building roof, the movement path of the runoff unit along the direction of the roof's gravitational potential energy gradient is determined. Based on the motion path and the area of ​​the discrete grid of the target building roof, the trajectory density of the runoff cells in each discrete grid is determined. Based on the changes in trajectory density during a continuous increase in the number of raindrop particles, determine whether the trajectory density has reached a stable state; Based on the correlation between the stabilized trajectory density, extreme rainfall parameters and raindrop particle dispersal intensity, the rainwater runoff in each area of ​​the target building roof is determined.

5. The method according to claim 4, characterized in that, Based on the motion path and the area of ​​the discrete grid of the target building roof, the trajectory density of runoff cells in each discrete grid is determined, including: Based on the movement path and the structural boundary and functional zoning results of the target building roof, the cross-zone flow trajectory of the runoff unit during its movement across the structural boundary or functional zone is determined. Based on the partitioning relationship of the discrete grid of the target building roof, an association mapping is established between the cross-regional flow trajectory and the upstream starting discrete grid and the downstream terminating discrete grid; The number of primary runoff unit trajectories formed by raindrop particles directly contacting the roof within each discrete grid, and the number of cross-regional runoff unit trajectories incorporated through the aforementioned correlation mapping are counted separately. By combining the number of trajectories of the primary runoff units, the number of trajectories of the cross-regional runoff units, and the area of ​​the corresponding discrete grid, the trajectory density of the runoff units in each discrete grid is determined.

6. The method according to claim 1, characterized in that, Based on the rainwater runoff, roof geometry, and gravity in each area of ​​the target building's roof, the rainwater thickness and rainwater load distribution in the corresponding areas are determined, including: Based on the rainwater runoff in each area of ​​the target building's roof, the roof runoff width and slope conditions of the corresponding area, the rainwater thickness of each area is determined. Based on the rain flow thickness, rainwater density, and gravitational acceleration, and combined with the projected area of ​​the discrete grid of the roof in each region, the roof rainwater load of the corresponding region is determined, and the rainwater load distribution of the target building roof is formed according to the roof rainwater load of each region.

7. A rainwater analysis device for building roofs, characterized in that, The device includes: The model building module is used to create a 3D model of the target building's roof. The first determining module is used to determine the rainwater runoff, rainwater thickness, and rainwater load distribution of each area of ​​the target building roof under multiple sets of wind and rain coupling conditions based on the three-dimensional model, multiple sets of wind and rain coupling parameters, the interaction characteristics between raindrop particles and the target building roof, and the physical characteristics of the target building roof. The multiple sets of wind and rain coupling conditions cover the combination scenarios of unfavorable wind direction, extreme wind speed, and extreme rainfall at different return periods in the area where the target building is located, and the parameter values ​​of the wind and rain coupling parameters corresponding to each set of wind and rain coupling conditions are different. The second determining module is used to determine the envelope extreme value of the rainwater effect on the roof of the target building based on the rainwater runoff, rainwater thickness and rainwater load distribution in each area of ​​the roof of the target building under the multiple sets of wind and rain coupling conditions. The analysis module is used to analyze the rainwater runoff characteristics and rainwater load of the target building roof based on the envelope extreme values. The first determining module is specifically used to determine the wind-rain coupled two-phase flow wind field within the computational domain of the target building and its roof based on the three-dimensional model and the wind-rain coupling parameters; determine the motion trajectory of raindrop particles based on the wind-rain coupled two-phase flow wind field; determine the rainwater runoff in each area of ​​the target building's roof based on the motion trajectory; and determine the rainwater runoff thickness and rainwater load distribution in the corresponding areas based on the rainwater runoff in each area of ​​the target building's roof, roof geometry, and gravity.

8. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the storage medium to perform the building roof rainwater analysis method as described in any one of claims 1-6.

9. An electronic device, characterized in that, The device includes at least one processor, at least one memory connected to the processor, and a bus; wherein the processor and the memory communicate with each other through the bus; the processor is used to call program instructions in the memory to execute the building roof rainwater analysis method as described in any one of claims 1-6.

Images