A method for assessing the risk of damage to glass curtain walls of urban buildings

Abstract

The present application relates to the technical field of urban building risk assessment, and specifically to a method for assessing the risk of damage to glass curtain walls of urban buildings. The present application firstly considers the influence of wind direction in simulating wind disasters in urban buildings, which can more objectively reflect the risk of regional wind disasters; then, when simulating flying objects, the three-dimensional characteristics of the urban space wind field are fully considered to ensure the accuracy of the glass curtain wall impact scenario; then, by constructing a database of building glass curtain wall collision scenarios, the risk of glass curtain wall damage is analyzed. That is, the present application realizes the accurate prediction and real-time assessment of the risk of damage to glass curtain walls in target urban building complexes through means such as refined data collection, three-dimensional model construction, physical process simulation, and probability analysis, providing strong support for the prevention and control of urban wind-induced disasters.

Description

Technical Field

[0001] The present application relates to the technical field of urban building risk assessment, and in particular to a method for assessing the risk of damage to a glass curtain wall of an urban building. Background Art

[0002] Under the influence of extreme meteorological disasters, randomly distributed debris objects (such as stones and loose building components) in urban spaces are swept by strong winds and fly rapidly in urban spaces, posing huge safety hazards to people and buildings.

[0003] Field surveys of previous strong wind disasters have shown that the losses and damages of high-rise buildings under wind disasters are mainly caused by the destruction of the enclosing structures, mainly glass curtain walls, under the action of flying objects. The damage of the glass curtain wall will further cause the property inside the building to be directly exposed to strong winds and heavy rains, causing a large amount of property losses. In order to minimize the disaster losses of urban high-rise buildings under strong wind disasters, insurance can be used to transfer wind disaster risks. In order to reasonably determine the insurance premium, it is necessary to accurately assess the risk of damage to the glass curtain walls of high-rise buildings under the action of flying objects. However, due to the low frequency of extreme meteorological disasters, actual statistical data is difficult to support accurate damage risks of glass curtain walls of high-rise buildings. Therefore, it is urgent to assess the wind damage risk of glass curtain walls of high-rise buildings through simulation. Summary of the invention

[0004] In order to avoid and overcome the technical problems existing in the prior art, the present application provides a method for assessing the risk of damage to a glass curtain wall of an urban building. The present application can accurately assess the risk of damage to a glass curtain wall.

[0005] To achieve the above objectives, this application provides the following technical solutions:

[0006] A method for assessing the risk of damage to a glass curtain wall of an urban building comprises the following assessment steps:

[0007] S1. Obtain the building layout data of the building complex in the target city, as well as the daily maximum wind speed and the wind direction of the daily maximum wind speed experienced on each day within a predetermined time period, and define the wind direction as the daily maximum wind direction; and the daily maximum wind speed and daily maximum wind direction of the same day are combined to form a set of wind speed and wind direction data;

[0008] S2. According to the multiple groups of wind speed and direction data obtained in step S1, a joint probability distribution of wind speed and direction of the target city building complex within a predetermined time period is obtained by statistics;

[0009] S3, based on the computational fluid dynamics method, combined with the building layout data obtained in step S1, construct an urban space three-dimensional model of the target city building complex; and input each group of wind speed and wind direction data obtained in step S1 into the urban space three-dimensional model separately, so as to obtain the urban space three-dimensional wind field corresponding to each group of wind speed and wind direction data;

[0010] S4, generating a number of flying objects in each of the three-dimensional wind fields of the urban space obtained in step S3, and counting the collision conditions between each flying object and each glass curtain wall; based on the statistical collision conditions, calculating and generating a wind speed and wind direction vulnerability surface of each glass curtain wall being damaged;

[0011] S5, using the total probability formula to perform probability analysis on the wind speed and wind direction joint probability distribution obtained in step S2 and the wind speed and wind direction vulnerability surface obtained in step S4, and obtain a probability model that characterizes the risk of each glass curtain wall being damaged under each group of wind speeds and wind directions through probability analysis;

[0012] S6. Input the wind speed and direction data of the target glass curtain wall in the target city building complex in the current environment into the probability model in step S5 to obtain the probability of the target glass curtain wall being damaged under the current wind speed and direction, and the probability represents the damage risk of the target glass curtain wall.

[0013] As a further solution of the present application: the process of generating a flight trajectory of a single flying parabolic object when flying in a three-dimensional wind field in an urban space is as follows:

[0014] S4A1. Obtaining three-dimensional wind field data in the urban space: obtaining wind speed data and wind direction data at each position at each moment in the three-dimensional wind field simulation result of the urban space where the flying object is currently located;

[0015] S4A2, applying a quasi-steady aerodynamic model: combining the wind speed data and wind direction data obtained in step S4A1, and the geometric characteristics of the flying object, using a quasi-steady aerodynamic model to calculate the aerodynamic force and torque exerted on the flying object at its current position in the three-dimensional wind field of the urban space;

[0016] S4A3, setting the initial conditions of the flying object: setting the initial position, initial velocity and initial rotational angular velocity of the flying object in the three-dimensional wind field of the urban space;

[0017] S4A4. Construct the dynamic equation: Construct the dynamic equation based on the aerodynamic force, torque, velocity of the flying object, mass of the flying object, and angular velocity of the flying object. The dynamic equation is expressed as follows:

[0018] ;

[0019] In the formula, It represents the aerodynamic force on the flying parabolic object in the three-dimensional wind field of the urban space, which is a vector;

[0020] Indicates the mass of the flying object;

[0021] represents the acceleration due to gravity;

[0022] It represents the speed of flying objects in the three-dimensional wind field of urban space, which is a vector;

[0023] Indicates speed In time t The first-order derivative of represents the acceleration of the flying object in the three-dimensional wind field of the urban space, which is a vector;

[0024] It represents the moment of force on the flying parabolic object in the three-dimensional wind field of the urban space, which is a vector;

[0025] It represents the angular velocity of the flying object in the three-dimensional wind field of the urban space, which is a vector;

[0026] It represents the moment of inertia of the flying object in the three-dimensional wind field of the urban space, which is a vector;

[0027] Indicates the angular velocity In time t The first-order derivative of represents the angular acceleration of the flying object in the three-dimensional wind field of the urban space, which is a vector;

[0028] S4A5, solving the dynamic equation: using the quasi-steady aerodynamic model in step S4A2 to calculate the aerodynamic force and torque of the flying object at the initial position at the current moment, and then substituting the initial velocity, initial rotational angular velocity, and aerodynamic force and torque at the initial position of the flying object into the dynamic equation, solving the dynamic equation by the Runge-Kutta method to update the position, velocity and rotational angular velocity of the flying object at the next moment;

[0029] S4A6, loop iteration: repeat the contents of steps S4A2 to S4A5, calculate the position, speed and angular velocity of the flying object at each moment in the three-dimensional wind field of the current urban space, and stop the iteration when the flying object collides with any glass curtain wall in the three-dimensional wind field of the current urban space; if the speed of the flying object is greater than the speed threshold of the glass curtain wall at this time, the glass curtain wall is destroyed; otherwise, the glass curtain wall is not destroyed; at the same time, smoothly connect each position point of the flying object from the initial position to the impact position in sequence, so as to form the flight trajectory of the flying object in the three-dimensional wind field of the current urban space.

[0030] As a further solution of this application: the specific steps of step S4 are as follows:

[0031] S41, analyzing a single urban space three-dimensional wind field: in the urban space three-dimensional wind field, a set number of flying objects are uniformly generated in the external area of ​​the building at the same time, and each flying object is processed at the same time according to the contents of steps S4A1 to S4A6, and the number of flying objects that damage each glass curtain wall is counted respectively; then the number is compared with the total number of flying objects, so as to obtain the probability of damage to each glass curtain wall under the current wind direction and wind speed conditions;

[0032] S42, repeatedly executing the contents of step S41 for several times, counting the probability of destruction of each glass curtain wall under the current wind direction and wind speed conditions, and simultaneously counting the number of occurrences of each destruction probability of each glass curtain wall under the current wind direction and wind speed conditions, and comparing the number with the total number of repeated executions, the occurrence probability of each destruction probability of each glass curtain wall under the current wind direction and wind speed conditions can be obtained;

[0033] S43, analyzing the three-dimensional wind field of the entire urban space: analyzing the three-dimensional wind field of the entire urban space according to the content in step S42, so as to obtain the probability of destruction of each glass curtain wall under each set of wind direction and wind speed conditions, and at the same time obtain the probability of occurrence of each destruction probability of each glass curtain wall under each set of wind direction and wind speed conditions;

[0034] S44, construct a three-dimensional model of wind speed and direction, wherein the wind speed and wind direction three-dimensional model uses wind speed as the horizontal coordinate, wind direction as the vertical coordinate, and the probability of occurrence of the probability of destruction as the vertical coordinate; then input the numerical value of the probability of occurrence obtained in step S43 into the three-dimensional model of wind speed and wind direction, and the surface formed by connecting the various coordinate points is the wind speed and wind direction vulnerability surface of each glass curtain wall being destroyed.

[0035] As a further solution of this application: the process of obtaining the wind speed and wind direction vulnerability surface of a single glass curtain wall under a single probability of being destroyed is as follows:

[0036] S441, obtaining all wind speeds, all wind directions, and all corresponding occurrence probabilities of the current glass curtain wall under the current probability of being destroyed, and storing them in a database of crash scenarios corresponding to the current glass curtain wall under the current probability of being destroyed;

[0037] The wind speeds in the crash scenario database are arranged in order from small to large, and the wind speed changes between adjacent wind speeds are The wind direction in the crashed scenario database refers to the angle between the current wind direction and the north direction in a clockwise direction, and the wind directions are arranged in order from small to large, and the wind direction changes between adjacent wind directions are ;

[0038] S442: Based on the wind speed and wind direction in the crashed scenario database in step S441, a standard orthogonal basis function for wind speed and wind direction is constructed, which is specifically expressed as follows:

[0039] ;

[0040] ;

[0041] ;

[0042] In the formula, Indicates that the current glass curtain wall is destroyed under the current probability. i Wind speed v i of n The standard orthogonal basis function of wind speed is i ∈[1, I ], n ∈[0, N ], I Indicates the total number of wind speed categories under the current probability of damage to the current glass curtain wall. N Indicates the maximum order of the standard orthogonal basis function of wind speed; v max Indicates the maximum wind speed of the current glass curtain wall under the current probability of being destroyed; is defined on [-1, 1] n Order Legendre polynomials; Indicates that the current glass curtain wall is destroyed under the current probability. j Wind direction of m The standard orthogonal basis function of the main wind direction is j ∈[1, J ], m ∈[0, M ], J Indicates the total number of wind direction categories of the current glass curtain wall under the current probability of being destroyed. M Indicates the maximum order of the standard orthogonal basis function of wind direction; Indicates that the current glass curtain wall is destroyed under the current probability. j Wind direction of m Order auxiliary wind direction standard orthogonal basis function; represents the sine function, represents the cosine function;

[0043] S443, based on the wind speed standard orthogonal basis function, the main wind direction standard orthogonal basis function and the auxiliary wind direction standard orthogonal basis function obtained in step S442, construct a wind speed and wind direction vulnerability surface analytical expression of the current glass curtain wall under the current probability of being destroyed, as follows:

[0044] ;

[0045] In the formula, Indicates that the current glass curtain wall is in wind speed and direction data When , the predicted value of the probability of occurrence of the current probability of being destroyed; and Both said Undetermined coefficient of order;

[0046] ;

[0047] ;

[0048] In the formula, Indicates that the current glass curtain wall is in wind speed and direction data When , the true value of the probability of occurrence of the current destruction probability;

[0049] S444, the wind speed, wind direction and occurrence probability in the crash scenario database in step S441 are sequentially substituted into the wind speed and wind direction vulnerability surface analytical expression in step S443, so as to obtain the predicted value of the occurrence probability of the current destruction probability of the current glass curtain wall when each set of wind speed and wind direction data is used;

[0050] By inputting all the predicted values ​​of the occurrence probability of the current glass curtain wall under the current destruction probability into the wind speed and wind direction three-dimensional model, the wind speed and wind direction vulnerability surface of each glass curtain wall being destroyed can be obtained. The analytical expression of the wind speed and wind direction vulnerability surface can also be used to predict the occurrence probability of the current destruction probability of the current glass curtain wall when it is in other wind speeds and wind directions outside the collision scenario database.

[0051] As a further solution of this application: the specific steps of step S2 are as follows:

[0052] S21, storing the maximum wind speeds of each day obtained in step S1 in a wind speed database in ascending order, and storing the maximum wind directions of each day in a wind direction database in ascending order;

[0053] S22. According to the distribution law of the daily maximum wind speed in the wind speed database, a distribution model of the daily maximum wind speed is determined, and each daily maximum wind speed in the wind speed database is input into the distribution model, and the optimal value of each distribution parameter of the distribution model is solved by maximum likelihood estimation, and the optimal value is assigned to the distribution model. The distribution model after the assignment is called the marginal probability distribution that conforms to the distribution law of the daily maximum wind speed, and the marginal probability distribution is defined as the wind speed marginal probability distribution;

[0054] S23, according to the distribution law of the daily maximum wind direction in the wind direction database, determine the distribution model of the daily maximum wind direction, and input each daily maximum wind direction in the wind direction database into the distribution model, solve the optimal value of each distribution parameter of the distribution model by maximum likelihood estimation, and assign the optimal value to the distribution model, the distribution model after the assignment is called the marginal probability distribution that conforms to the distribution law of the daily maximum wind direction, and the marginal probability distribution is defined as the wind direction marginal probability distribution;

[0055] S24, select a Copula function, and combine it with the wind speed marginal probability distribution obtained in step S22 and the wind direction marginal probability distribution obtained in step S23 to form a joint distribution; and input the data in the wind speed database and the wind direction database into the joint distribution, solve the optimal value of each distribution parameter of the joint distribution by maximum likelihood estimation, and assign the optimal value to the joint distribution. The joint distribution after the assignment is called a joint probability distribution of wind speed and wind direction that can simultaneously describe the marginal distribution characteristics of wind speed and wind direction, as well as the correlation between them.

[0056] As a further solution of the present application: the building layout data includes the shape, size, location of the building, and the topographic data of the location of the target building complex.

[0057] As a further solution of this application: the specific content of step S3 is as follows:

[0058] S31, selecting a three-dimensional modeling software, and inputting the building layout data of the target building complex into the three-dimensional modeling software to construct a three-dimensional model of the urban space of the target urban building complex;

[0059] S32. In computational fluid dynamics software, a rectangular flow field is constructed, and the three-dimensional model of the urban space is placed in the flow field;

[0060] S33, making the wind blow toward the three-dimensional urban space model along the length direction of the flow field, and simulating different wind directions by rotating the three-dimensional urban space model in the flow field;

[0061] S34, inputting each set of wind speed and wind direction data into the flow field of step S33, so as to obtain the three-dimensional wind field of the urban space composed of the flow field and the three-dimensional model of the urban space under the current wind speed and wind direction conditions.

[0062] As a further solution of the present application: In the computational fluid dynamics software, the three-dimensional wind field in the urban space will simulate the wind speed and direction data of the flying objects at any time and any position in the three-dimensional wind field in the urban space according to the currently input wind speed and direction data.

[0063] As a further solution of this application: the specific steps of step S5 are as follows:

[0064] S51. Calculate wind speed and direction data through joint probability distribution of wind speed and direction Probability of occurrence ;

[0065] S52, calculate the current glass curtain wall under the wind speed and wind direction data through the wind speed and wind direction vulnerability surface analytical expression When the current probability of being destroyed is B The predicted value of the probability of occurrence is expressed as ;

[0066] S53: The probability calculated in step S51 and the value calculated in step S52 Input it into the total probability formula to calculate the current probability of the glass curtain wall being destroyed under each group of wind speeds and wind directions. B The probability model of the occurrence probability calculates the probability of occurrence to represent the risk of glass curtain wall damage.

[0067] As a further solution of this application: the probability model is specifically expressed as follows:

[0068] ;

[0069] In the formula, Indicates the probability of the current glass curtain wall being damaged under each set of wind speeds and wind directions B probability of occurrence.

[0070] Compared with the prior art, the beneficial effects of this application are:

[0071] 1. This application first considers the influence of wind direction in simulating urban building wind disasters, which can more objectively reflect the risk of regional wind disasters; then, when simulating flying objects, it fully considers the three-dimensional characteristics of the urban space wind field to ensure the accuracy of the glass curtain wall collision scenario; then, by constructing a database of building glass curtain wall collision scenarios, the risk of glass curtain wall damage is analyzed. That is, this application achieves accurate prediction and real-time evaluation of the risk of glass curtain wall damage in the target urban building complex through refined data collection, three-dimensional model construction, physical process simulation, and probability analysis, providing strong support for the prevention and control of urban wind-induced disasters.

[0072] 2. This application provides highly accurate basic data for risk assessment by obtaining detailed building layout data of the target city's building complexes, as well as the maximum wind speed and direction of each day during a specific time period. This refined data collection method ensures the accuracy and reliability of subsequent analysis.

[0073] 3. Based on the collected wind speed and direction data, the statistically obtained joint probability distribution of wind speed and direction can fully reflect the wind environment conditions that the target city building complex may encounter within the predetermined time period. This probability distribution not only takes into account the size of the wind speed, but also combines the influence of wind direction, providing a more comprehensive perspective for risk assessment.

[0074] 4. The three-dimensional model of urban space constructed by computational fluid dynamics methods, combined with actual wind speed and direction data, can simulate the real wind field environment. This simulation method can intuitively show the flow of wind in urban space and provide a scientific basis for evaluating wind-induced disasters.

[0075] 5. By generating flying objects in a three-dimensional wind field and counting their collisions with the glass curtain wall, the vulnerability of the glass curtain wall under different wind speeds and directions can be quantitatively evaluated. This simulation method based on physical processes can more accurately reflect the destructive potential of wind-induced flying objects on the glass curtain wall, providing an important basis for risk assessment.

[0076] 6. The joint probability distribution of wind speed and direction is combined with the wind speed and direction vulnerability surface through the full probability formula to construct a probability model that characterizes the risk of damage to each glass curtain wall under each group of wind speed and wind direction. This probability model can comprehensively consider multiple factors (such as wind speed, wind direction, building layout, etc.) to accurately predict the damage risk of the target glass curtain wall.

[0077] 7. By inputting the wind speed and direction in the current environment into the probability model, the probability of damage to the target glass curtain wall under the current conditions can be quickly obtained. This real-time risk assessment capability enables managers to quickly respond to wind-induced disaster risks and take necessary preventive and response measures to ensure the safety of personnel and property. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 This is the evaluation flow chart for this application.

[0079] Figure 2 This is a probability density distribution diagram of wind speed and direction in the embodiment of this application.

[0080] Figure 3 It is a three-dimensional model of the architectural space in the embodiment of this application.

[0081] Figure 4 It is a top view of the three-dimensional model of the architectural space in the embodiment of the present application.

[0082] Figure 5 This is a diagram showing the calculation domain settings for CFD simulation in an embodiment of the present application.

[0083] Figure 6 This is a simulation result diagram of the three-dimensional wind field in the urban space at a wind direction of 105° and a wind speed of 65m / s in the embodiment of the present application.

[0084] Figure 7 This is a flight trajectory diagram within a three-dimensional wind field in an urban space in an embodiment of the present application.

[0085] Figure 8 These are the four facade impact result diagrams of the target building in the embodiment of this application.

[0086] Fig. 9 This is a vulnerability surface diagram of wind speed and direction when the probability of damage is 0.1% in the embodiment of the present application.

[0087] Fig.10 This is a vulnerability surface diagram of wind speed and direction when the probability of damage is 0.2% in the embodiment of the present application.

[0088] Fig.11 This is a vulnerability surface diagram of wind speed and direction when the probability of damage is 0.5% in the embodiment of the present application.

[0089] Fig.12 This is a graph showing the annual damage rate of the glass curtain wall in the embodiment of the present application. DETAILED DESCRIPTION

[0090] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0091] See also Figure 1 , this application includes the following contents.

[0092] 1. Obtain building layout data and wind speed and direction data.

[0093] Obtain the building layout data of the target city building complex, and the daily maximum wind speed and wind direction of the daily maximum wind speed experienced every day within a predetermined time period, and define the wind direction as the daily maximum wind direction; and the daily maximum wind speed and daily maximum wind direction of the same day form a set of wind speed and direction data. The specific steps are as follows:

[0094] S11. Obtaining building layout data: The building layout data of the target city building complex can be obtained by any of the following methods;

[0095] Public data: Many cities will make public building layout data, including building location, height, shape and other information.

[0096] Geographic Information System Data: Detailed building layout data can be obtained through professional GIS platforms or software.

[0097] Satellite imagery and remote sensing technology: Using high-resolution satellite imagery or drone aerial imagery, combined with image recognition technology, building layout information can be extracted.

[0098] Extract key information, such as the building’s latitude and longitude coordinates, height, floor space, etc., and organize the extracted data into a structured format, such as CSV, JSON, or a database table, for subsequent analysis.

[0099] S12, obtain wind speed and direction data: obtain the maximum wind speed and direction of each day in a predetermined time period. In the embodiment of the present application, the wind direction and speed data in the area where the target building complex is located is obtained in a year, and analyzed year by year according to the method of the present application.

[0100] The daily maximum wind speed and the corresponding wind direction are extracted from the daily wind speed and wind direction data recorded by the weather station. The daily maximum wind speed and the daily maximum wind direction are combined into a set of wind speed and wind direction data.

[0101] You can use programming languages ​​such as Python for data processing and storage, such as using the Pandas library to process data tables.

[0102] 2. Construct the probability density distribution of wind speed and direction.

[0103] Based on the above-obtained wind speed and direction data, the joint probability distribution of wind speed and direction of the target city building complex within the predetermined time period is obtained. The specific steps are as follows:

[0104] S21. The maximum wind speeds of each day obtained are sequentially stored in a wind speed database in ascending order, and the maximum wind directions of each day are sequentially stored in a wind direction database in ascending order.

[0105] S22. Use statistical methods (such as histograms, QQ plots, etc.) to preliminarily determine the distribution model of the daily maximum wind speed data (such as Weibull distribution, lognormal distribution, etc.). Then, input each daily maximum wind speed in the wind speed database into the distribution model, solve the optimal value of each distribution parameter of the distribution model through maximum likelihood estimation, and assign the optimal value to the distribution model. The distribution model after assignment is called the marginal probability distribution that conforms to the distribution law of the daily maximum wind speed, and the marginal probability distribution is defined as the wind speed marginal probability distribution.

[0106] Maximum likelihood estimation is a method to find the parameter value that maximizes the probability of the model generating the data under given data. In the process of solving the problem using maximum likelihood estimation, the goodness of fit is evaluated and the final goodness of fit is kept within the set range to ensure that the selected distribution model can better describe the statistical characteristics of the wind speed data.

[0107] S23. Daily maximum wind direction data are usually cyclic (i.e., 0° and 360° represent the same direction), so it may be necessary to use circular statistical methods (such as circular histograms) to fit their distribution.

[0108] The daily maximum wind direction data may not be a continuous variable, but a discrete variable (such as 8 or 16 directions). Therefore, it is necessary to select a suitable discrete distribution model for fitting according to the specific situation of the daily maximum wind direction data. The maximum likelihood estimation method is also used to fit the marginal probability distribution of wind direction, and the marginal probability distribution is defined as the marginal probability distribution of wind direction.

[0109] S24. According to the characteristics of the daily maximum wind speed and daily maximum wind direction data (such as correlation, tail dependence, etc.), select a suitable binary Copula function. Common Copula functions include Gaussian Copula, t-Copula, Clayton Copula, etc. The selected Copula function is combined with the wind speed marginal probability distribution obtained in step S22 and the wind direction marginal probability distribution obtained in step S23 to form a joint distribution. The data in the wind speed database and the wind direction database are input into the joint distribution, and the optimal values ​​of the distribution parameters of the joint distribution are solved by maximum likelihood estimation, and the optimal values ​​are assigned to the joint distribution. The joint distribution after assignment is called a wind speed and wind direction joint probability distribution that can simultaneously describe the marginal distribution characteristics of wind speed and wind direction and the correlation between them.

[0110] 3. Establish a three-dimensional wind field in the urban space.

[0111] Based on the computational fluid dynamics method, combined with the above-obtained building layout data, the urban space three-dimensional model of the target city building complex is constructed. Each set of wind speed and wind direction data is separately input into the urban space three-dimensional model to obtain the urban space three-dimensional wind field corresponding to each set of wind speed and wind direction data. The specific steps are as follows:

[0112] S31. Select the building height, location (latitude and longitude or relative coordinates), shape (such as rectangle, circle, etc.), and possible building surface material properties (affecting the wind resistance coefficient) from the building layout data obtained above and input them into the 3D modeling software. If necessary, terrain data (such as elevation map) should also be collected to more accurately reflect the impact of urban terrain on the wind field.

[0113] Select appropriate 3D modeling software (such as AutoCAD, SketchUp, Revit, etc.) or CFD pre-processing software (such as ANSYS Meshing, STAR-CCM+ Pre-Processor, etc.), and then build each building one by one in the three-dimensional space according to the building layout data, and adjust its position, height and shape to construct a three-dimensional model of the urban space that forms the target city building complex.

[0114] During the modeling process, appropriate simplification can be performed to improve computational efficiency while ensuring that building details (such as windows, balconies, etc.) have little impact on the overall wind field.

[0115] S32. In the computational fluid dynamics software, use the meshing tool to mesh the urban space 3D model to construct a rectangular flow field, and place the urban space 3D model in the flow field. Encrypt the mesh around the building and in areas where the wind speed changes dramatically to improve the calculation accuracy.

[0116] S33. Set the boundary conditions and initial conditions of the flow field:

[0117] a. Boundary conditions:

[0118] According to the wind speed and direction data obtained above, the wind speed and direction at the flow field entrance are set.

[0119] Set boundary conditions for the flow domain outlet and other boundaries (such as the sides and top), which can usually be pressure outlet or free flow conditions.

[0120] b. Initial conditions:

[0121] Set the initial wind speed and direction of the entire flow field, which are usually the same or close to the inlet boundary conditions.

[0122] The wind is made to blow toward the three-dimensional model of the urban space along the length direction of the flow field, and different wind directions are simulated by rotating the three-dimensional model of the urban space in the flow field.

[0123] S34. Input each group of wind speed and direction data into the flow field domain of step S33 respectively, select a suitable solver (such as a pressure-based solver or a density-based solver) and a turbulence model (such as a k-ε model, LES, etc.) to perform multiple simulation calculations, so as to obtain a three-dimensional wind field of the urban space composed of the flow field domain and the three-dimensional model of the urban space under the current wind speed and direction conditions.

[0124] 4. Construct the vulnerability surface of wind speed and direction.

[0125] Generate a number of flying objects in the three-dimensional wind field of each urban space, and count the collisions between each flying object and each glass curtain wall; based on the statistical collisions, calculate and generate the wind speed and direction vulnerability surface of each glass curtain wall that is damaged. The specific steps are as follows:

[0126] S41. Since a three-dimensional wind field in an urban space represents a set of wind speed and direction data, the three-dimensional wind field in all urban spaces can be mapped by analyzing a single three-dimensional wind field in the urban space.

[0127] Analyze a single urban space in three dimensions: Generate a set number of flying objects evenly and simultaneously in the external area of ​​the building in the three-dimensional wind field of the urban space, and process each flying object at the same time according to the contents of steps S4A1 to S4A6, and count the number of flying objects that damage each glass curtain wall respectively; then compare this number with the total number of flying objects to obtain the probability of damage to each glass curtain wall under the current wind direction and wind speed conditions.

[0128] S4A1. Obtaining three-dimensional wind field data in the urban space: obtaining wind speed data and wind direction data at each position at each moment in the three-dimensional wind field simulation results in the urban space where the flying object is currently located.

[0129] S4A2. Applying a quasi-steady aerodynamic model: combining the wind speed data and wind direction data obtained in step S4A1, as well as the geometric characteristics of the flying object, using a quasi-steady aerodynamic model to calculate the aerodynamic force and torque exerted on the flying object at its current position in the three-dimensional wind field of the urban space.

[0130] S4A3. Set the initial conditions of the flying object: set the initial position, initial velocity and initial rotational angular velocity of the flying object in the three-dimensional wind field of the urban space.

[0131] S4A4. Construct the dynamic equation: Construct the dynamic equation based on the aerodynamic force, torque, speed of the flying object, mass of the flying object, and angular velocity of the flying object. The dynamic equation is shown in formula (1):

[0132] (1).

[0133] S4A5. During the simulation of the three-dimensional wind field in each urban space, the three-dimensional wind field in the urban space will simulate the wind speed data and wind direction data of the flying objects at any time and any position in the three-dimensional wind field in the urban space according to the currently input wind speed and wind direction data;

[0134] Solve the dynamic equations: Use the quasi-steady aerodynamic model in step S4A2 to calculate the aerodynamic force and torque of the flying object at the initial position at the current moment, then substitute the initial velocity, initial angular velocity of the flying object, and the aerodynamic force and torque at the initial position into the dynamic equations, and solve the dynamic equations by the Runge-Kutta method to update the position, velocity and angular velocity of the flying object at the next moment.

[0135] S4A6, loop iteration: repeat steps S4A2 to S4A5, calculate the position, speed and angular velocity of the flying object at each moment in the three-dimensional wind field of the current urban space, and stop the iteration when the flying object collides with any glass curtain wall in the three-dimensional wind field of the current urban space; if the speed of the flying object is greater than the speed threshold of the glass curtain wall at this time, the glass curtain wall is destroyed; otherwise, the glass curtain wall is not destroyed; at the same time, smoothly connect each position point of the flying object from the initial position to the impact position in sequence, so as to form the flight trajectory of the flying object in the three-dimensional wind field of the current urban space.

[0136] S42, repeat the contents of step S41 for several times, count the destruction probabilities of each glass curtain wall under the current wind direction and wind speed conditions, and simultaneously count the number of times each destruction probability of each glass curtain wall occurs under the current wind direction and wind speed conditions, and compare the number with the total number of repeated executions to obtain the occurrence probability of each destruction probability of each glass curtain wall under the current wind direction and wind speed conditions.

[0137] S43, analyzing the three-dimensional wind field of the entire urban space: analyzing the three-dimensional wind field of the entire urban space according to the content of step S32 to obtain the probability of damage of each glass curtain wall under each set of wind direction and wind speed conditions, and at the same time obtain the probability of occurrence of each damage probability of each glass curtain wall under each set of wind direction and wind speed conditions.

[0138] S44, construct a three-dimensional model of wind speed and direction, wherein the three-dimensional model has wind speed as the horizontal coordinate, wind direction as the vertical coordinate, and the probability of occurrence of the probability of destruction as the vertical coordinate; then the numerical value of the probability of occurrence obtained in step S33 is input into the three-dimensional model of wind speed and direction, and the wind speed and direction vulnerability surface of each glass curtain wall being destroyed can be obtained.

[0139] The process of obtaining the wind speed and direction vulnerability surface of a single glass curtain wall under a single destruction probability is as follows:

[0140] S441. Obtain all wind speeds, all wind directions, and all corresponding occurrence probabilities of the current glass curtain wall under the current probability of being destroyed, and store them in a database of crash scenarios corresponding to the current glass curtain wall under the current probability of being destroyed.

[0141] The wind speeds in the crash scenario database are arranged in order from small to large, and the wind speed changes between adjacent wind speeds are The wind direction in the crash scenario database refers to the angle between the current wind direction and the true north direction in a clockwise direction, and the wind directions are arranged in order from small to large, and the wind direction changes between adjacent wind directions are .

[0142] S442: Based on the wind speed and wind direction in the crash scenario database in step S441, a standard orthogonal basis function for wind speed and wind direction is constructed, as shown in formulas (2) to (4):

[0143] (2);

[0144] (3);

[0145] (4).

[0146] S443, based on the wind speed standard orthogonal basis function, the main wind direction standard orthogonal basis function and the auxiliary wind direction standard orthogonal basis function obtained in step S442, construct a wind speed and wind direction vulnerability surface analytical expression of the current glass curtain wall under the current probability of being destroyed, as follows:

[0147] ;

[0148] In the formula, Indicates that the current glass curtain wall is in wind speed and direction data When , the predicted value of the probability of occurrence of the current probability of being destroyed; and Both said Undetermined coefficient of order;

[0149] ;

[0150] ;

[0151] In the formula, Indicates that the current glass curtain wall is in wind speed and direction data , the true value of the probability of occurrence of the current destruction probability.

[0152] S444, the wind speed, wind direction and occurrence probability in the crash scenario database in step S441 are sequentially substituted into the wind speed and wind direction vulnerability surface analytical expression in step S443, so as to obtain the predicted value of the occurrence probability of the current destruction probability of the current glass curtain wall when each set of wind speed and wind direction data is used;

[0153] By inputting all the predicted values ​​of the occurrence probability of the current glass curtain wall under the current destruction probability into the wind speed and wind direction three-dimensional model, the wind speed and wind direction vulnerability surface of each glass curtain wall being destroyed can be obtained. The analytical expression of the wind speed and wind direction vulnerability surface can also be used to predict the occurrence probability of the current destruction probability of the current glass curtain wall when it is in other wind speeds and wind directions outside the collision scenario database.

[0154] 5. Build a probability model.

[0155] The total probability formula is used to perform probability analysis on the obtained wind speed and wind direction joint probability distribution and wind speed and wind direction vulnerability surface, and a probability model is obtained through probability analysis to characterize the risk of each glass curtain wall being damaged under each group of wind speed and wind direction. The specific steps are as follows:

[0156] S51. Calculate wind speed and direction data through joint probability distribution of wind speed and direction Probability of occurrence .

[0157] S52, calculate the current glass curtain wall under the wind speed and wind direction data through the wind speed and wind direction vulnerability surface analytical expression When the current probability of being destroyed is B The predicted value of the probability of occurrence is expressed as .

[0158] S53, the calculated probability and Input it into the total probability formula to calculate the current probability of the glass curtain wall being destroyed under each group of wind speeds and wind directions. B The probability model of the occurrence probability is used to calculate the probability of occurrence, and the probability of occurrence calculated by the probability model represents the risk of glass curtain wall damage. The probability model is specifically shown in formula (5):

[0159] (5);

[0160] Through the analysis from step S51 to step S53, the probability of any glass curtain wall being damaged under each set of wind speeds and wind directions can be calculated.

[0161] 6. Calculate the risk of being compromised.

[0162] By inputting the wind speed and direction in the current environment of the target glass curtain wall in the target city building complex into the probability model, the probability of the target glass curtain wall being damaged under the current wind speed and direction can be obtained, and this probability represents the damage risk of the target glass curtain wall.

[0163] 7. Implementation examples.

[0164] 7.1. Obtain building layout data and wind speed and direction data.

[0165] The building layout data of the target city building complex is obtained through the geographic information system data. The daily maximum wind speed and daily maximum wind direction data of the meteorological observation station near the target city building complex are obtained every day for 15 consecutive years through the meteorological data network.

[0166] 7.2. Construct the probability density function of wind speed and direction.

[0167] The maximum likelihood estimation method is used to fit the marginal probability distribution function of the daily maximum wind speed and the daily maximum wind direction. The daily maximum wind speed adopts the Gumbel probability distribution model, and the daily maximum wind direction adopts the third-order harmonic function probability distribution model. Frank Copula is used to fit the correlation structure of wind speed and direction data, and then the joint probability density distribution of wind speed and direction is obtained, as shown in Figure 2 shown.

[0168] 7.3. Establish a three-dimensional wind field in the urban space.

[0169] The target urban building complex analyzed in this embodiment includes the target building and other buildings around it. The target building is a high-rise building with a length of 52.5m, a width of 49.5m, and a height of 100m. There are 49 other buildings of different heights distributed within a range of 300m × 300m around it, such as Figure 3 shown. Figure 3 The X-axis in the figure represents the distance from the center of the target to the origin along the east-west direction, and the positive direction of the X-axis is due east. Figure 3 The Y-axis in the figure represents the distance from the center of the target to the origin along the north-south direction, and the positive direction of the Y-axis is due north. Figure 3 The Z axis in the figure represents the height of the target building, and the positive direction of the Z axis is vertically upward. The four glass curtain walls of the target building are all composed of 1.5 m × 2.5 m glass units. Each glass curtain wall is composed of 1360 glass units, that is, a total of 5440 glass units, and they are numbered in sequence from 0 to 5440.

[0170] This embodiment can simulate different wind direction angles by rotating the target urban building complex, such as Figure 4 shown. Figure 4 The X-axis in the figure represents the distance from the center of the target to the origin along the east-west direction, and the positive direction of the X-axis is due east. Figure 4 The Y-axis in the figure represents the distance from the center of the target to the origin along the north-south direction, and the positive direction of the Y-axis is due north. Figure 4 The Height in the figure represents the height of the target building, and its specific value is represented by a scale. The CFD numerical calculation domain established for the target urban building complex is as follows: Figure 5 As shown, the hybrid grid technology is used to divide the flow field. Hexahedral units are used in the central area of ​​the flow field, tetrahedral grids are used in the area close to the building geometry, and multi-layer prismatic grids are used on the ground and building surfaces to capture the boundary layer flow field information.

[0171] The average wind speed, turbulent kinetic energy and energy dissipation rate profile at the flow field inlet are determined according to the average surface wind speed and ground roughness, and then the three-dimensional wind field in the urban space is numerically solved based on the RANS k-epsilon model. Figure 6As shown, these are the streamlines in the three-dimensional wind field in the urban space when the maximum daily wind direction is 105° and the maximum daily wind speed is 65 m / s.

[0172] 7.4. Construct the wind speed and direction vulnerability surface.

[0173] 1) Figure 7 For example, multiple flying objects are set in the three-dimensional wind field of the urban space. The state variables such as the initial position, initial rotation angular velocity, and initial velocity of the flying objects at the initial moment are obtained. Figure 7 The meaning of each coordinate axis in Figure 3 The same as in.

[0174] 2) In the i In a time step, according to the current position of the flying object, the wind speed at the current position is obtained by interpolation in the three-dimensional wind field simulation results in the urban space, and the aerodynamic force and torque of the flying object are calculated according to the angular velocity combined with the quasi-steady aerodynamic model, and the dynamic equation is constructed by combining the aerodynamic force, torque and state variables.

[0175] 3) Solve the dynamic equations through the Runge-Kutta method to update the position, velocity and angular velocity of the flying object at the next moment.

[0176] 4) Repeat steps 2) to 3) until the flying object hits the glass curtain wall and destroys it or flies out of the calculation domain.

[0177] 5) The actual possible wind speed range of the daily maximum wind speed is [0, 65 m / s]. To cover this wind speed range, discrete wind speed conditions are considered, including 10 m / s, 15 m / s, 20 m / s, 25 m / s, 30 m / s, 35 m / s, 40 m / s, 45 m / s, 50 m / s, 55 m / s, 60 m / s and 65 m / s. The wind direction range of the daily maximum wind direction is [0°, 360°). To cover this wind direction range, discrete wind direction conditions are considered, including 0°, 15°, 30°, 45°, 60°, 75°, 90°, 105°, 120°, 135°, 150°,

[0178] 165°, 180°, 195°, 210°, 225°, 240°, 255°, 270°, 285°, 300°, 315°, 330° and 345°. A total of 288 wind speed and direction conditions are formed by the above discrete wind speed conditions and wind direction conditions.

[0179] 6) For each wind speed and wind direction condition, the CFD numerical method is first used to simulate the three-dimensional wind field in the urban space under the given daily maximum wind speed and daily maximum wind direction conditions, and then 10,000 groups of high-rise building glass curtain wall impact scenarios are randomly generated. The specific method is as follows:

[0180] (1) According to the initial distribution probability model of flying objects, 100,000 flying objects are randomly generated in the urban space.

[0181] (2) For i A flying projectile is calculated.

[0182] (3) Determine the i The flight trajectory of the first parabola is j piece( j = 1, 2, ···, 5440) The geometric relationship of the glass unit, if the i The flying object landed at j If the impact velocity of a glass curtain wall unit is greater than the set velocity threshold, the j A glass unit was damaged.

[0183] (4) Traverse 5440 glass units to determine the i The impact of a flying projectile on a glass curtain wall.

[0184] (5) Traverse 100,000 flying objects to determine the damage of the glass curtain wall under the action of all flying objects, thereby forming a set of glass curtain wall impact scenarios;

[0185] Figure 8 The flight trajectories of projectiles hitting the glass curtain wall in a set of impact scenarios under the conditions of 105° wind direction and 65 m / s wind speed are given in Figure 2. Figure 8 It can be seen that most of the flying objects hit the windward side of the target building, that is, the north facade, during their flight. Figure 8 The specific crash scenarios of the four sides of the target building are given in Figure 8 In the figure, it can be seen that the north facade has been damaged the most times.

[0186] (6) Repeat steps (1) to (5) 10,000 times to generate 10,000 sets of glass curtain wall impact scenarios, and count the number of times the current glass curtain wall is damaged in these 10,000 sets of impact scenarios, thereby obtaining the probability of damage to the current glass curtain wall under the current wind speed and direction conditions.

[0187] 7) Perform operations according to the contents of step 6) for each wind speed and wind direction working condition to obtain the probability of damage to the current glass curtain wall under each current wind speed and wind direction working condition.

[0188] 8) According to the contents of step 6) to step 7), each glass curtain wall is operated 1000 times under each wind speed and wind direction condition, and the probability of each destruction probability occurring in these 1000 times is counted, and this probability is the occurrence probability. This embodiment considers the case where the probability of glass curtain wall being destroyed is 0.1%, 0.2% and 0.5%, respectively. Figure 9-11 The wind speed and direction vulnerability surface is shown.

[0189] 7.5. Calculate the risk of being compromised.

[0190] According to the total probability formula, combined with the wind speed and wind direction probability density distribution constructed in 7.2 and the wind speed and wind direction vulnerability surface constructed in 7.4, the damage risk of the target glass curtain wall can be obtained.

[0191] According to the above 7.1-7.5, analyze year by year, and then average it for 15 years to get the annual probability of damage risk of the target glass curtain wall, such as Fig.12 As shown. Fig.12 It can be seen that the greater the annual damage rate, the lower the probability of its occurrence, which means that the probability of glass curtain walls in current cities being damaged by flying objects is low.

[0192] The above is only a preferred specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can make equivalent substitutions or changes within the technical scope disclosed in the present application according to the technical solution and inventive concept of the present application, which should be covered by the protection scope of the present application.

Claims

1. A method for assessing the risk of damage to a glass curtain wall of an urban building, characterized in that: The assessment steps include: S1. Obtain the building layout data of the building complex in the target city and its daily maximum wind speed and the daily maximum wind direction of the daily maximum wind speed within a predetermined time period; and the daily maximum wind speed and daily maximum wind direction of the same day are combined to form a set of wind speed and direction data; S2. Statistically analyze the wind speed and direction data to obtain the joint probability distribution of wind speed and direction of the target urban building complex; S3. Combine the building layout data to construct a three-dimensional urban space model of the target city building complex; input each set of wind speed and direction data into the three-dimensional urban space model to obtain the corresponding three-dimensional urban space wind field; S4, generating a number of flying objects in the three-dimensional wind field of each urban space, and counting the collision conditions between each flying object and each glass curtain wall; based on the collision conditions, obtaining the wind speed and wind direction vulnerability surface of each glass curtain wall being damaged; S5. Use the total probability formula to perform probability analysis on the joint probability distribution of wind speed and direction and the vulnerability surface of wind speed and direction to obtain a probability model that characterizes the risk of each glass curtain wall being damaged under each group of wind speeds and directions; S6. Input the wind speed and direction data of the target glass curtain wall in the current environment into the probability model to obtain the damage risk of the target glass curtain wall under the current wind speed and direction.

2. The method for assessing the risk of damage to a glass curtain wall of an urban building according to claim 1, characterized in that: The process of a single flying object generating a flight trajectory when flying in the three-dimensional wind field of the urban space is as follows: S4A1. Obtaining three-dimensional wind field data in the urban space: obtaining wind speed data and wind direction data at each position at each moment in the three-dimensional wind field simulation result of the urban space where the flying object is currently located; S4A2, applying a quasi-steady aerodynamic model: combining the wind speed data and wind direction data obtained in step S4A1, and the geometric characteristics of the flying object, using a quasi-steady aerodynamic model to calculate the aerodynamic force and torque exerted on the flying object at its current position in the three-dimensional wind field of the urban space; S4A3, setting the initial conditions of the flying object: setting the initial position, initial velocity and initial rotational angular velocity of the flying object in the three-dimensional wind field of the urban space; S4A4. Construct the dynamic equation: Construct the dynamic equation based on the aerodynamic force, torque, velocity of the flying object, mass of the flying object, and angular velocity of the flying object. The dynamic equation is expressed as follows: ； In the formula, It represents the aerodynamic force on the flying parabolic object in the three-dimensional wind field of the urban space, which is a vector; Indicates the mass of the flying object; represents the acceleration due to gravity; It represents the speed of flying objects in the three-dimensional wind field of urban space, which is a vector; Indicates speed In time t The first-order derivative of represents the acceleration of the flying object in the three-dimensional wind field of the urban space, which is a vector; It represents the moment of force on the flying parabolic object in the three-dimensional wind field of the urban space, which is a vector; It represents the angular velocity of the flying object in the three-dimensional wind field of the urban space, which is a vector; It represents the moment of inertia of the flying object in the three-dimensional wind field of the urban space, which is a vector; Indicates the angular velocity In time t The first-order derivative of represents the angular acceleration of the flying object in the three-dimensional wind field of the urban space, which is a vector; S4A5, solving the dynamic equation: using the quasi-steady aerodynamic model in step S4A2 to calculate the aerodynamic force and torque of the flying object at the initial position at the current moment, and then substituting the initial velocity, initial rotational angular velocity, and aerodynamic force and torque at the initial position of the flying object into the dynamic equation, solving the dynamic equation by the Runge-Kutta method to update the position, velocity and rotational angular velocity of the flying object at the next moment; S4A6, loop iteration: repeat the contents of steps S4A2 to S4A5, calculate the position, speed and angular velocity of the flying object at each moment in the three-dimensional wind field of the current urban space, and stop the iteration when the flying object collides with any glass curtain wall in the three-dimensional wind field of the current urban space; if the speed of the flying object is greater than the speed threshold of the glass curtain wall at this time, the glass curtain wall is destroyed; otherwise, the glass curtain wall is not destroyed; at the same time, smoothly connect each position point of the flying object from the initial position to the impact position in sequence, so as to form the flight trajectory of the flying object in the three-dimensional wind field of the current urban space.

3. The method for assessing the risk of damage to a glass curtain wall of an urban building according to claim 2, characterized in that: The specific steps of step S4 are as follows: S41, analyzing a single urban space three-dimensional wind field: in the urban space three-dimensional wind field, a set number of flying objects are uniformly generated in the external area of ​​the building at the same time, and each flying object is processed at the same time according to the contents of steps S4A1 to S4A6, and the number of flying objects that damage each glass curtain wall is counted respectively; then the number is compared with the total number of flying objects, so as to obtain the probability of damage to each glass curtain wall under the current wind direction and wind speed conditions; S42, repeatedly executing the contents of step S41 for several times, counting the probability of destruction of each glass curtain wall under the current wind direction and wind speed conditions, and simultaneously counting the number of occurrences of each destruction probability of each glass curtain wall under the current wind direction and wind speed conditions, and comparing the number with the total number of repeated executions, the occurrence probability of each destruction probability of each glass curtain wall under the current wind direction and wind speed conditions can be obtained; S43, analyzing the three-dimensional wind field of the entire urban space: analyzing the three-dimensional wind field of the entire urban space according to the content in step S42, so as to obtain the probability of destruction of each glass curtain wall under each set of wind direction and wind speed conditions, and at the same time obtain the probability of occurrence of each destruction probability of each glass curtain wall under each set of wind direction and wind speed conditions; S44, construct a three-dimensional model of wind speed and direction, wherein the wind speed and wind direction three-dimensional model uses wind speed as the horizontal coordinate, wind direction as the vertical coordinate, and the probability of occurrence of the probability of destruction as the vertical coordinate; then input the numerical value of the probability of occurrence obtained in step S43 into the three-dimensional model of wind speed and wind direction, and the surface formed by connecting the various coordinate points is the wind speed and wind direction vulnerability surface of each glass curtain wall being destroyed.

4. The method for assessing the risk of damage to a glass curtain wall of an urban building according to claim 3, characterized in that: The process of obtaining the wind speed and direction vulnerability surface of a single glass curtain wall under a single destruction probability is as follows: S441, obtaining all wind speeds, all wind directions, and all corresponding occurrence probabilities of the current glass curtain wall under the current probability of being destroyed, and storing them in a database of crash scenarios corresponding to the current glass curtain wall under the current probability of being destroyed; The wind speeds in the crash scenario database are arranged in order from small to large, and the wind speed changes between adjacent wind speeds are The wind direction in the crashed scenario database refers to the angle between the current wind direction and the north direction in a clockwise direction, and the wind directions are arranged in order from small to large, and the wind direction changes between adjacent wind directions are ; S442: Based on the wind speed and wind direction in the crashed scenario database in step S441, a standard orthogonal basis function for wind speed and wind direction is constructed, which is specifically expressed as follows: ； ； ； In the formula, Indicates that the current glass curtain wall is destroyed under the current probability. i Wind speed v i of n The standard orthogonal basis function of wind speed is i ∈[1, I ], n ∈[0, N ], I Indicates the total number of wind speed categories under the current probability of damage to the current glass curtain wall. N Indicates the maximum order of the standard orthogonal basis function of wind speed; v max Indicates the maximum wind speed of the current glass curtain wall under the current probability of being destroyed; is defined on [-1, 1] n Order Legendre polynomials; Indicates that the current glass curtain wall is destroyed under the current probability. j Wind direction of m The standard orthogonal basis function of the main wind direction is j ∈[1, J ], m ∈[0, M ], J Indicates the total number of wind direction categories of the current glass curtain wall under the current probability of being destroyed. M Indicates the maximum order of the standard orthogonal basis function of wind direction; Indicates that the current glass curtain wall is destroyed under the current probability. j Wind direction of m Order auxiliary wind direction standard orthogonal basis function; represents the sine function, represents the cosine function; S443, based on the wind speed standard orthogonal basis function, the main wind direction standard orthogonal basis function and the auxiliary wind direction standard orthogonal basis function obtained in step S442, construct a wind speed and wind direction vulnerability surface analytical expression of the current glass curtain wall under the current probability of being destroyed, as follows: ； In the formula, Indicates that the current glass curtain wall is in wind speed and direction data When , the predicted value of the probability of occurrence of the current probability of being destroyed; and Both said Undetermined coefficient of order; ； ； In the formula, Indicates that the current glass curtain wall is in wind speed and direction data When , the true value of the probability of occurrence of the current destruction probability; S444, the wind speed, wind direction and occurrence probability in the crash scenario database in step S441 are sequentially substituted into the wind speed and wind direction vulnerability surface analytical expression in step S443, so as to obtain the predicted value of the occurrence probability of the current destruction probability of the current glass curtain wall when each set of wind speed and wind direction data is used; By inputting all the predicted values ​​of the occurrence probability of the current glass curtain wall under the current destruction probability into the wind speed and wind direction three-dimensional model, the wind speed and wind direction vulnerability surface of each glass curtain wall being destroyed can be obtained. The analytical expression of the wind speed and wind direction vulnerability surface can also be used to predict the occurrence probability of the current destruction probability of the current glass curtain wall when it is in other wind speeds and wind directions outside the collision scenario database.

5. A method for assessing the risk of damage to a glass curtain wall of an urban building according to any one of claims 1 to 4, characterized in that: The specific steps of step S2 are as follows: S21, storing the maximum wind speeds of each day obtained in step S1 in a wind speed database in ascending order, and storing the maximum wind directions of each day in a wind direction database in ascending order; S22. According to the distribution law of the daily maximum wind speed in the wind speed database, a distribution model of the daily maximum wind speed is determined, and each daily maximum wind speed in the wind speed database is input into the distribution model, and the optimal value of each distribution parameter of the distribution model is solved by maximum likelihood estimation, and the optimal value is assigned to the distribution model. The distribution model after the assignment is called the marginal probability distribution that conforms to the distribution law of the daily maximum wind speed, and the marginal probability distribution is defined as the wind speed marginal probability distribution; S23, according to the distribution law of the daily maximum wind direction in the wind direction database, determine the distribution model of the daily maximum wind direction, and input each daily maximum wind direction in the wind direction database into the distribution model, solve the optimal value of each distribution parameter of the distribution model by maximum likelihood estimation, and assign the optimal value to the distribution model, the distribution model after the assignment is called the marginal probability distribution that conforms to the distribution law of the daily maximum wind direction, and the marginal probability distribution is defined as the wind direction marginal probability distribution; S24, select a Copula function, and combine it with the wind speed marginal probability distribution obtained in step S22 and the wind direction marginal probability distribution obtained in step S23 to form a joint distribution; and input the data in the wind speed database and the wind direction database into the joint distribution, solve the optimal value of each distribution parameter of the joint distribution by maximum likelihood estimation, and assign the optimal value to the joint distribution. The joint distribution after the assignment is called a joint probability distribution of wind speed and wind direction that can simultaneously describe the marginal distribution characteristics of wind speed and wind direction, as well as the correlation between them.

6. The method for assessing the risk of damage to a glass curtain wall of an urban building according to claim 5, characterized in that: Building layout data includes the shape, size, location of the building, and terrain data of the location of the target building complex.

7. The method for assessing the risk of damage to a glass curtain wall of an urban building according to claim 6, characterized in that: The specific content of step S3 is as follows: S31, selecting a three-dimensional modeling software, and inputting the building layout data of the target building complex into the three-dimensional modeling software to construct a three-dimensional model of the urban space of the target urban building complex; S32. In computational fluid dynamics software, a rectangular flow field is constructed, and the three-dimensional model of the urban space is placed in the flow field; S33, making the wind blow toward the three-dimensional urban space model along the length direction of the flow field, and simulating different wind directions by rotating the three-dimensional urban space model in the flow field; S34, inputting each set of wind speed and wind direction data into the flow field of step S33, so as to obtain the three-dimensional wind field of the urban space composed of the flow field and the three-dimensional model of the urban space under the current wind speed and wind direction conditions.

8. The method for assessing the risk of damage to a glass curtain wall of an urban building according to claim 7, characterized in that: In computational fluid dynamics software, the three-dimensional wind field in the urban space will simulate the wind speed and direction data of the flying objects at any time and any position in the three-dimensional wind field in the urban space according to the currently input wind speed and direction data.

9. The method for assessing the risk of damage to a glass curtain wall of an urban building according to claim 8, characterized in that: The specific steps of step S5 are as follows: S51. Calculate wind speed and direction data through joint probability distribution of wind speed and direction Probability of occurrence ; S52, calculate the current glass curtain wall under the wind speed and wind direction data through the wind speed and wind direction vulnerability surface analytical expression When the current probability of being destroyed is B The predicted value of the probability of occurrence is expressed as ; S53: The probability calculated in step S51 and the value calculated in step S52 Input it into the total probability formula to calculate the current probability of the glass curtain wall being destroyed under each group of wind speeds and wind directions. B The probability model of the occurrence probability calculates the probability of occurrence to represent the risk of glass curtain wall damage.

10. The method for assessing the risk of damage to a glass curtain wall of an urban building according to claim 9, characterized in that: The probability model is specifically expressed as follows: ； In the formula, Indicates the probability of the current glass curtain wall being damaged under each set of wind speeds and wind directions B probability of occurrence.

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