A method for determining wind load of large-span building design based on control atlas

Abstract

The application provides a large-span building design wind load determination method based on a control atlas, relates to the technical field of building engineering wind resistance design and computational fluid dynamics numerical simulation, and the method is to obtain roof pressure coefficients of multiple working condition fluid dynamics calculation to construct a database; target calculation working conditions are determined by comparing extreme values, and a roof wind load control atlas is constructed; adjacent calculation units are continuously merged in space based on the atlas and a pressure difference threshold value, and control areas are identified; key control working conditions are extracted according to area proportion ratios; region representative pressure values are calculated according to the key control working conditions, and then design wind loads are determined. The application solves the problems that in the existing large-span building wind load design, a large number of CFD calculation working conditions are directly subjected to point-by-point maximum value envelope, resulting in that the design result is too conservative, and that the wind pressure partition is divided depending on artificial experience, resulting in low efficiency and strong subjectivity.

Description

Technical Field

[0001] This invention relates to the field of wind-resistant design and computational fluid dynamics numerical simulation technology for building engineering, and particularly to a method for determining wind loads in the design of large-span buildings based on control charts. Background Technology

[0002] Currently, large-span buildings (such as airport terminals, stadiums, large convention centers, and logistics warehouses) experience extremely complex wind load distributions due to their large spans and complex shapes. In engineering practice, computational fluid dynamics (CFD) numerical simulations are typically used to determine their wind loads. In existing engineering design processes, a three-dimensional geometric model of the building to be analyzed is usually established first. Then, corresponding CFD calculation models are established independently for various incoming wind directions, wind speed levels, and different building operating states (such as combinations of closed, partially open, and fully open doors and windows) to obtain wind pressure distribution data on the roof under each calculation condition.

[0003] After obtaining a large number of calculation results, the existing processing method is usually to calculate the peak pressure coefficient for the wind pressure results under all calculation conditions according to the requirements of relevant building codes, and then perform point-by-point envelope processing for each calculation condition. That is to say, for any spatial location on the building roof, the designer will extract the wind pressure value that causes the most unfavorable stress at that location from all conditions as the final design wind load for that point. For example, if dozens of wind directions and various opening states are considered, it may be necessary to complete nearly a hundred or even hundreds of independent CFD calculations, and finally directly take the maximum value of all calculation results point by point to form the design wind load.

[0004] However, this traditional approach has significant drawbacks. First, existing methods assume that all calculated load cases contribute equally to the final design, ignoring the extremely low probability of certain extreme opening conditions occurring in actual operation. Second, using a point-by-point maximum envelope method leads to overly conservative design wind loads. This is because the most unfavorable stresses in different areas of the roof are often controlled by completely unrelated load cases (e.g., load case A controls the northwest corner, load case B controls the southeast corner). In actual physical wind fields, these extreme pressure distributions are unlikely to occur simultaneously; forcibly superimposing them makes the overall design overly conservative. Third, among dozens or even hundreds of load cases, only a few are truly critical control conditions that determine the overall design result, while the vast majority of load cases, despite consuming significant computational resources, fail to enter the final envelope, lacking an effective means of automatically identifying critical load cases. Finally, CFD software outputs a continuous grid pressure field, while structural engineers actually need discrete design wind pressure zones and corresponding design pressure values. Currently, this conversion process mainly relies on manual experience, which is inefficient and prone to introducing subjective errors. Summary of the Invention

[0005] To address the aforementioned shortcomings in existing technologies, this invention provides a method for determining wind loads in large-span building designs based on control graphs. This method solves the problems in existing large-span building wind load designs, where directly applying the maximum value envelope to a large number of CFD calculation cases leads to overly conservative design results, and relying on manual experience to divide wind pressure zones results in low efficiency and high subjectivity.

[0006] To achieve the aforementioned objectives, the technical solution adopted by this invention is as follows: a method for determining wind loads in the design of large-span buildings based on control charts, comprising: S1: Based on the fluid dynamics calculation results of the large-span building under multiple calculation conditions, obtain the pressure coefficient of each calculation unit of the roof of the large-span building under each calculation condition, and construct a roof wind pressure database; S2: Using the roof wind pressure database, the pressure coefficients of each calculation unit under all calculation conditions are compared to extreme values ​​to determine the target calculation condition that causes the calculation unit to generate the design control pressure. A mapping relationship is established between each calculation unit and its corresponding target calculation condition to construct the roof wind load control map. S3: Based on the roof wind load control map, perform spatial continuity analysis on each calculation unit, and merge calculation units with the same target calculation conditions and pressure difference between adjacent calculation units less than the preset pressure threshold to identify multiple control areas covering the roof. S4: For each control area, statistically analyze the target calculation conditions corresponding to its internal calculation units, establish a mapping relationship between the control area and the target calculation conditions, and extract the key control conditions based on the proportion of the total area of ​​the control area corresponding to each target calculation condition to the total roof area. S5: Based on the extracted key control conditions and corresponding control areas, calculate the regional representative pressure value of each control area to obtain the regional design wind load of the large-span building, and complete the determination of the design wind load of the large-span building.

[0007] Further, S1 includes: A three-dimensional geometric model is established based on the architectural structure of the large-span building to be analyzed, and calculation conditions including multiple incoming wind directions and various building operating states are determined according to the design wind environment. For each calculation condition, a corresponding fluid dynamics calculation model is established to perform fluid dynamics calculations, and the fluid dynamics calculation results are obtained. The pressure coefficient of each calculation unit of the large-span building roof under each calculation condition is analyzed. The pressure coefficient and the corresponding calculated operating condition information are linked and stored to construct a roof wind pressure database.

[0008] Further, S2 includes: Using the roof wind pressure database, the pressure coefficients of each calculation unit under all calculation conditions are extracted; The pressure coefficient of each calculation unit under all calculation conditions is compared with the extreme values ​​in turn. The calculation condition that causes the corresponding calculation unit to generate the maximum negative pressure is determined as the target calculation condition, and the number of the target calculation condition is assigned to the corresponding calculation unit. Based on the numbering of all calculation units and their corresponding target calculation conditions, a control matrix covering the roof is established, and the control matrix is ​​used as the roof wind load control map.

[0009] Further, S3 includes: Based on the roof wind load control map, all calculation units on the roof are traversed, and calculation units with the same target calculation conditions and adjacent spatial locations are selected as candidate regions. The pressure difference between adjacent computing units in the candidate region is compared. When the pressure difference between adjacent computing units is less than the preset pressure threshold, the corresponding computing units are merged. When the pressure difference between adjacent computing units is greater than or equal to the preset pressure threshold, they are divided into different regions to obtain the result of merging adjacent computing units. The merged results of adjacent computing units are identified to obtain multiple control areas that cover the roof and have a unified target computing condition inside.

[0010] Further, S4 includes: For each control area, the target computing condition number corresponding to its internal computing unit is counted, and a mapping relationship between the control area and the target computing condition is established. Based on the mapping relationship between control regions and target calculation conditions, all control regions corresponding to each target calculation condition are extracted, and the total control area corresponding to each target calculation condition is calculated. Calculate the proportion of the total controlled area to the total roof area corresponding to each target calculation condition, and based on the proportion, eliminate the target calculation conditions that do not meet the preset area proportion conditions and / or the corresponding control areas are discontinuous to obtain the remaining target calculation conditions. The remaining target calculation conditions that meet the preset area ratio conditions and whose corresponding control areas are continuous are used to extract the key control conditions.

[0011] Further, S5 includes: Based on the extracted key control conditions and corresponding control regions, extract the pressure coefficients of all calculation units in each control region under its corresponding key control conditions. Based on the pressure coefficients of all calculation units in each control area under its corresponding key control conditions, the regional representative pressure value of each control area is obtained by using at least one of the following methods: regional maximum pressure coefficient, regional average pressure coefficient, or regional area weighted pressure coefficient. The regional representative pressure values ​​of each control area are used as the design pressure values ​​of the corresponding areas. The regional design wind loads of large-span buildings are then determined by summarizing these values, thus completing the determination of the design wind loads for large-span buildings.

[0012] The beneficial effects of this invention are as follows: This invention provides a method for determining wind loads in the design of large-span buildings based on control maps. By comparing the extreme values ​​of the pressure coefficients of each calculation unit under all calculation conditions, the target calculation condition is determined and a mapping relationship is established, thus constructing a roof wind load control map for the first time. This method intuitively correlates and expresses the extreme control information traditionally hidden in a large amount of CFD fluid dynamics calculation results, clearly defining the truly controlled external conditions at each discrete location on the roof, and providing a clear data foundation for subsequent data processing.

[0013] Based on the constructed roof wind load control map, spatial continuity analysis of the calculation units is performed, and a preset pressure threshold is introduced to merge adjacent units with the same target calculation conditions. This process transforms wind pressure zoning from traditional division based on engineers' manual experience to purely data-driven automatic clustering, fully reflecting the spatial continuity and local differences in complex roof wind pressure distribution, and improving the objectivity and automation of regional division.

[0014] Based on establishing the mapping relationship between the control area and the target calculation conditions, the key control conditions are automatically screened and extracted by statistically analyzing the proportion of the total area of ​​the control area corresponding to the target calculation conditions to the total roof area. This step can automatically identify the core conditions that truly play a decisive role in the distribution of wind loads on the roof, avoiding interference from a large number of non-control conditions in the final design results and effectively reducing the scale of data involved in subsequent calculations and analyses.

[0015] Finally, based on the extracted key control conditions and corresponding control areas, the regional representative pressure values ​​of each control area are calculated to determine the design wind load. This method uses continuous control areas rather than single discrete points as the load determination object, ensuring the physical consistency between the design load and the actual control wind field. It fundamentally overcomes the overly conservative problem caused by the traditional point-by-point extreme value envelope, which forcibly superimposes local extreme values ​​of unrelated conditions, thus improving the rationality of engineering design. Attached Figure Description

[0016] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein: Figure 1 This is an exemplary flowchart illustrating a method for determining wind loads in the design of large-span buildings based on control charts, according to some embodiments of this specification. Detailed Implementation

[0017] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0018] Example Figure 1 This is an exemplary flowchart illustrating a method for determining wind loads in the design of large-span buildings based on control charts, according to some embodiments of this specification. Figure 1 As shown, the process includes the following steps. In some embodiments, the process may be executed by a processor.

[0019] S1: Based on the fluid dynamics calculation results of the large-span building under multiple calculation conditions, obtain the pressure coefficient of each calculation unit of the roof of the large-span building under each calculation condition, and construct a roof wind pressure database.

[0020] Large-span buildings are complex architectural structures with large span dimensions, spacious interiors, and sensitivity to wind loads. Examples of large-span buildings include airport terminals, stadiums, large convention centers, and logistics warehouses—building types that need to withstand complex wind pressure distributions.

[0021] In some embodiments, the processor can obtain the structural foundation data of a large-span building by receiving the building structure parameters and project location information input by the user, and then use it as the initial input object for wind load calculation for subsequent 3D modeling and stress analysis.

[0022] A computational case refers to a specific combination of computational conditions set during fluid dynamics numerical simulation to comprehensively evaluate the stress conditions of a building under different external environments and internal usage conditions. For example, a computational case may include multiple incoming wind directions and various building operating states, which may include different opening combinations such as closed doors and windows, partially open doors and windows, fully open doors and windows, open skylights, and open smoke exhaust windows.

[0023] In some embodiments, the processor can obtain the design wind environment data of the location of the large-span building to be analyzed, and combine it with the actual possible opening operation state of the building to generate a series of combination conditions of wind direction and opening state, thereby obtaining the calculation conditions.

[0024] Computational fluid dynamics (CFD) results refer to the set of physical quantities characterizing the flow field and structural forces output after numerical simulation of a large-span building model under specific boundary conditions using computational fluid dynamics methods. For example, CFD results may include continuous pressure field data of the roof of a large-span building under various computational conditions, the distribution of pressure coefficients of each element, and the corresponding pressure time history data.

[0025] In some embodiments, the processor can establish a fluid dynamics calculation model for each specific calculation condition, and perform iterative calculations under uniform parameters such as calculation domain size, mesh generation principle and boundary conditions, and finally extract the converged simulation data to obtain the fluid dynamics calculation results.

[0026] A computational cell refers to the basic geometric grid or minimum analysis region divided from the spatial discretization of the surface of a large-span building roof during numerical simulation or wind load analysis. For example, a computational cell may include a tiny planar polygonal region generated during the meshing process of a 3D model, which has an independent number, spatial coordinate information, and is capable of independently bearing and recording surface wind pressure data.

[0027] In some embodiments, the processor can read the three-dimensional geometric model of a large-span building, perform geometric discretization on the roof surface of the model according to preset mesh division size and mesh type requirements, and divide the continuous roof surface into several non-overlapping small regions to obtain computing units.

[0028] The pressure coefficient of each computational unit on the roof of a large-span building under each computational condition is a dimensionless value that characterizes the relative pressure on the surface of the discretized grid of the roof under the influence of wind flow, given a specific combination of wind direction and building opening conditions. For example, the pressure coefficient of each computational unit on the roof of a large-span building under each computational condition can include the average pressure coefficient, extreme pressure coefficient, and time-history characteristic values ​​of pressure fluctuations for each unit.

[0029] In some embodiments, the processor can extract the converged surface static pressure data of the flow field by performing a fluid dynamics numerical simulation, and then perform a ratio calculation with the incoming flow pressure at a reference height, thereby obtaining the pressure coefficient of each calculation unit of the large-span building roof under each calculation condition for each discrete grid point or grid surface.

[0030] A roof wind pressure database is a comprehensive information collection used to structurally store wind pressure-related data generated after numerical simulations of large-span buildings under all specified operating conditions. For example, a roof wind pressure database may include the pressure coefficient of each calculation unit, the wind direction angle of the corresponding operating condition, building operating status information, and pressure time history data, with the calculation condition number as the main index.

[0031] In some embodiments, after completing the numerical simulation of all calculation conditions, the processor can collect and organize the pressure coefficients and related configuration information of each calculation unit on the roof under each condition, classify and associate them according to the condition number, and persistently store them in a preset storage medium, thereby establishing and obtaining a roof wind pressure database.

[0032] In some embodiments, the processor can establish a three-dimensional geometric model based on the building structure of the large-span building to be analyzed, and determine the calculation conditions including multiple incoming wind directions and multiple building operating states according to the design wind environment; establish a corresponding fluid dynamics calculation model for each calculation condition to perform fluid dynamics calculations, obtain fluid dynamics calculation results, and analyze the pressure coefficient of each calculation unit on the roof of the large-span building under each calculation condition; associate and store the pressure coefficient and the corresponding calculation condition information to construct a roof wind pressure database.

[0033] A three-dimensional geometric model is a digital structural representation used in computer virtual space to accurately express the three-dimensional shape, spatial dimensions, and external contour features of a large-span building to be analyzed. For example, a three-dimensional geometric model may include the building's roof surface shape, facade structure, details of auxiliary components, and three-dimensional spatial coordinate data of the location of door and window openings that can reflect the connection between the building's internal and external spaces.

[0034] In some embodiments, the processor can receive architectural design drawings or 3D scan point cloud data imported by the user, perform surface construction and solid modeling operations on the building's exterior outline according to the building's structural form, and assign corresponding geometric dimension parameters to generate a 3D geometric model.

[0035] The design wind environment refers to the atmospheric boundary layer flow field characteristics and meteorological statistical parameters surrounding the site of the project to be constructed, which serve as the external environmental input conditions for the wind-resistant design of the structure. For example, the design wind environment may include parameters such as the basic wind pressure at the project site, the surface roughness category, the wind speed profile distribution at different heights, and the possible angles of multiple incoming wind directions.

[0036] In some embodiments, the processor can obtain meteorological statistics and geomorphological features corresponding to the geographical location of the large-span building to be analyzed by querying meteorological observation databases or retrieving relevant national building structure load codes, and then analyze and determine the design wind environment.

[0037] S2: Using the roof wind pressure database, the pressure coefficients of each calculation unit under all calculation conditions are compared to extreme values ​​to determine the target calculation condition that causes the calculation unit to generate the design control pressure. A mapping relationship is established between each calculation unit and its corresponding target calculation condition to construct the roof wind load control map.

[0038] The pressure coefficient of each computational unit under all computational conditions refers to the aggregated set of all pressure coefficient values ​​generated by simulating each basic geometric grid on the roof under all preset wind direction and opening state combinations. For example, the pressure coefficient of each computational unit under all computational conditions may include multiple sets of extreme and average pressure values ​​corresponding to a specific roof grid point under different operating states such as closed and fully open doors and windows, as well as different incoming wind direction angles.

[0039] In some embodiments, the processor can access the pre-built roof wind pressure database, use the independent number of the computing unit as the search condition, and traverse to extract the simulated wind pressure results data of all working conditions recorded by the computing unit in the database, thereby obtaining the pressure coefficient of each computing unit under all computing working conditions.

[0040] A target calculation condition refers to a specific combination of conditions among all preset calculation conditions that will result in the most unfavorable stress state for a particular calculation unit on the roof or achieve the design control targets. For example, a target calculation condition may include a specific combination of wind direction angles and building operating states that will cause the surface of the calculation unit to generate the maximum negative pressure extreme value, the maximum positive pressure extreme value, or cause its comprehensive control pressure to reach the peak value.

[0041] In some embodiments, the processor can sequentially extract the pressure coefficients of a computing unit under all computing conditions, sort these pressure coefficient values ​​by size and compare extreme values, and filter out the operating condition number that causes the pressure maximum value to occur, thereby determining the target computing condition.

[0042] The mapping relationship between a computational unit and its corresponding target computational load case refers to the one-to-one correspondence established between a geometrically discrete point on the roof space and its most unfavorable external environmental conditions. For example, the mapping relationship between a computational unit and its corresponding target computational load case may include a pairing data set between each roof grid number with independent spatial coordinates and its corresponding specific load case number that can generate design control pressure.

[0043] In some embodiments, after determining the target computing condition for each computing unit, the processor can directly assign the number of the target computing condition as attribute information to the corresponding computing unit, and bind the unit identifier and the condition identifier in the data structure, thereby establishing and obtaining the mapping relationship between the computing unit and the corresponding target computing condition.

[0044] A roof wind load control map is a collection of spatial control relationship data that comprehensively presents and records information on the most unfavorable controlled conditions at various spatial locations on the roof. For example, a roof wind load control map may include control matrix data covering the entire roof of a large-span building. This map not only records the control condition numbers at various locations on the roof but also reflects the actual control range distribution of different conditions across the entire roof space.

[0045] In some embodiments, the processor can construct and obtain a roof wind load control map by summarizing the mapping relationship between all computing units and the corresponding target computing conditions, assembling and matrixing all computing units with the condition number attribute according to their actual spatial position in the roof three-dimensional model.

[0046] In some embodiments, the processor can utilize the roof wind pressure database to extract the pressure coefficients of each computing unit under all computing conditions; sequentially compare the extreme values ​​of the pressure coefficients of each computing unit under all computing conditions to determine the computing condition that causes the corresponding computing unit to generate the maximum negative pressure as the target computing condition, and assign the number of the target computing condition to the corresponding computing unit; based on the numbers of all computing units and their corresponding target computing conditions, establish a control matrix covering the roof, and use the control matrix as the roof wind load control map.

[0047] A control matrix is ​​a data structure organized and expressed in two-dimensional or multi-dimensional array form, recording the controlled operating condition number corresponding to each discrete grid point on the building roof. For example, a control matrix may include a data array indexed by the spatial row and column coordinates of the computing unit and with the target computing operating condition number determined by each computing unit as the element value, intuitively reflecting which operating condition controls each area.

[0048] In some embodiments, the processor can generate a control matrix by traversing all determined computing units and their corresponding target computing conditions, and filling the target computing condition numbers into the corresponding positions of a predefined multidimensional array according to the geometric topology of the computing units or the grid numbering order.

[0049] S3: Based on the roof wind load control map, perform spatial continuity analysis on each calculation unit, and merge calculation units with the same target calculation conditions and pressure difference between adjacent calculation units less than the preset pressure threshold to identify multiple control areas covering the roof.

[0050] A pressure threshold is a critical reference value used to determine whether there is a significant change in local wind pressure characteristics between adjacent calculation units when dividing a roof control zone. For example, a pressure threshold may include a fixed pressure difference value set based on engineering design experience, or a pressure coefficient difference limit that allows for fluctuations, calculated based on the statistical results of pressure gradients across all calculation units.

[0051] In some embodiments, the processor can obtain a pressure threshold by receiving empirical parameters pre-input by the designer or by adaptively calculating and extracting a value that can distinguish between pressure abrupt changes and continuous changes by analyzing the overall gradient changes of wind pressure on the surface of a large-span building.

[0052] A control area is a continuous planar region on a building roof composed of multiple computational units that share the same target calculation conditions, are spatially adjacent, and have relatively stable internal wind pressure variations. For example, a control area may include a contiguous roof panel area corresponding to a specific wind direction and a fully open configuration, where the pressure differences between adjacent computational units are all within allowable ranges. This area has uniform control conditions and similar pressure variation characteristics.

[0053] In some embodiments, the processor can compare the pressure differences between adjacent computing units in the candidate area, and merge them when the pressure difference between adjacent units is less than a preset pressure threshold. After continuous traversal and merging, multiple control areas covering the roof are finally identified.

[0054] In some embodiments, the processor can traverse all computing units on the roof based on the roof wind load control map, and select computing units with the same target computing conditions and adjacent spatial locations as candidate regions; compare the pressure differences between adjacent computing units within the candidate regions, and merge the corresponding computing units when the pressure difference between adjacent computing units is less than a preset pressure threshold; when the pressure difference between adjacent computing units is greater than or equal to the preset pressure threshold, divide them into different regions to obtain the adjacent computing unit merging results; identify the adjacent computing unit merging results to obtain multiple control regions covering the roof and having a unified target computing condition inside.

[0055] A candidate region refers to a set of computational cells that, during the initial stage of spatial continuity analysis, meet the requirements of consistent operating conditions and are spatially connected, but have not yet undergone internal wind pressure difference testing. For example, a candidate region may include a group of continuously connected computational cells on the roof whose target computational operating condition number is A and which share edges or vertices in the geometric mesh topology.

[0056] In some embodiments, the processor can traverse all the calculation units in the entire roof wind load control map, read the target calculation condition number of each unit, extract the calculation units with the same condition number and in an adjacent and connected state in three-dimensional space and divide them into a group to obtain candidate regions.

[0057] The adjacent computational unit merging result refers to the grouped state data formed after performing internal pressure gradient verification on the candidate region, merging the units that meet the requirements together, and separating the units that do not meet the requirements. For example, the adjacent computational unit merging result may include a list of units that have been confirmed as a whole control block after pressure difference comparison, and a list of independent units or sub-regions that have been separated from the original candidate region due to excessive pressure difference.

[0058] In some embodiments, the processor can calculate the pressure difference between adjacent computing units sharing a boundary within a candidate region and compare it with a preset pressure threshold. If the pressure difference is less than the threshold, the processor marks them as the same group in the data structure for fusion. If the pressure difference is greater than or equal to the threshold, the processor cuts off their group association and divides them into different regions. After completing all comparisons, the processor outputs the result of merging adjacent computing units.

[0059] S4: For each control area, statistically analyze the target calculation conditions corresponding to its internal calculation units, establish a mapping relationship between the control area and the target calculation conditions, and extract the key control conditions based on the proportion of the total area of ​​the control area corresponding to each target calculation condition to the total roof area.

[0060] The mapping relationship between the control area and the target calculation condition refers to the corresponding connection established between the aggregated continuous roof block and the specific external calculation condition under unified control. For example, the mapping relationship between the control area and the target calculation condition may include a corresponding data pair between a control block identifier containing attributes such as area and location coordinates, and the wind direction and opening status condition number that generate the maximum negative pressure, which are common to all calculation units within it.

[0061] In some embodiments, the processor can establish a mapping relationship between the control region and the target computing condition by statistically analyzing all computing units contained within each identified control region, extracting the target computing condition number common to these computing units, assigning the operating condition number to the control region as a whole, and establishing an association pointer between the region object and the operating condition object.

[0062] Critical control cases refer to the set of core control cases among all target calculation cases that play a major controlling role in the overall wind load distribution of a large-span building roof, and that have a large actual control area or good continuity. For example, critical control cases may include combinations of several specific wind directions and building door and window states that represent the main wind pressure distribution characteristics of the roof after being filtered by area and continuity, excluding redundant cases that only control scattered small areas.

[0063] In some embodiments, the processor can obtain key control conditions by statistically analyzing the total area of ​​the control area corresponding to each target calculation condition and calculating its proportion to the total roof area, eliminating conditions where the proportion does not meet the conditions or the control area is discontinuous, and then extracting the remaining conditions that have a substantial impact on the design.

[0064] In some embodiments, the processor can, for each control region, count the target computing condition numbers corresponding to its internal computing units and establish a mapping relationship between control regions and target computing conditions; based on the mapping relationship between control regions and target computing conditions, extract all control regions corresponding to each target computing condition and count the total control area corresponding to each target computing condition; calculate the ratio of the total control area corresponding to each target computing condition to the total roof area, and based on the ratio, eliminate target computing conditions that do not meet the preset area ratio condition and / or whose corresponding control regions are discontinuous, to obtain the remaining target computing conditions; extract the key control conditions from the remaining target computing conditions whose ratio meets the preset area ratio condition and whose corresponding control regions are continuous.

[0065] The total control area refers to the sum of the physical areas of all control zones that can be controlled on the entire building roof under a specific target calculation condition. For example, the total control area may include the sum of the areas controlled by condition B located in the northwest corner of the roof and another area located in the middle of the roof, reflecting the actual extent of the influence of this condition on the overall roof stress.

[0066] In some embodiments, the processor can extract all control regions belonging to a certain target computing condition based on the established mapping relationship, read the area attribute parameters of each control region and perform cumulative summation to calculate the total control area corresponding to the target computing condition.

[0067] The remaining target calculation conditions refer to the set of conditions temporarily retained for further confirmation after the initial screening and elimination of all target calculation conditions based on area ratio or continuity conditions during the extraction of key conditions. For example, the remaining target calculation conditions may include a list of condition numbers that whose controlled area as a percentage of the total roof area exceeds a pre-set minimum limit, are not judged as completely invalid or fragmented controls, and are included in the subsequent final screening and judgment process.

[0068] In some embodiments, the processor can calculate the total control area ratio of each target computing condition, compare the ratio data with the preset area ratio conditions, and directly delete or mark the data nodes of those conditions that do not meet the conditions from memory, thereby obtaining the remaining target computing conditions retained in the processing queue.

[0069] Preset area ratio conditions refer to the minimum threshold or evaluation rules used to determine whether a calculation condition qualifies as a critical control condition, specifying the percentage of its controlled area relative to the total area. For example, preset area ratio conditions may include setting a percentage value, such as stipulating that the controlled area of ​​a single condition must be greater than 5% of the total roof area, or a comprehensive ratio judgment logic based on the dispersion of the controlled areas to eliminate minor conditions with minimal impact on the overall design.

[0070] In some embodiments, the processor can receive specific percentage threshold data pre-input into the system configuration interface by structural design engineers based on past experience in designing large-span buildings or relevant industry standards, and then perform parsing and storage operations to obtain preset area ratio conditions.

[0071] S5: Based on the extracted key control conditions and corresponding control areas, calculate the regional representative pressure value of each control area to obtain the regional design wind load of the large-span building, and complete the determination of the design wind load of the large-span building.

[0072] The regional representative pressure value refers to one or a set of equivalent representative values ​​calculated and extracted from all discrete wind pressure data within each defined control area to meet the requirements of structural stress analysis and engineering design. For example, the regional representative pressure value may include values ​​that reflect the overall wind pressure characteristics of the area, such as the regional maximum pressure coefficient, regional average pressure coefficient, or regional area-weighted pressure coefficient, obtained by mathematically processing the pressure coefficients of all grid cells within the control area.

[0073] In some embodiments, the processor can extract the pressure coefficients of all computing units within the control area based on the corresponding key control conditions, and perform mathematical operations such as finding extreme values, arithmetic averages, or weighted averages with grid area as the weight on these coefficient values ​​according to the built-in design specification algorithm, thereby calculating the representative pressure value of the area.

[0074] Regional design wind load refers to the standard wind pressure load values ​​distributed across various roof control zones, ultimately used for wind-resistant design and mechanical stress analysis of large-span building structures. For example, regional design wind load can include actual physical pressure values ​​directly applied to surface loads, nodal loads, and component loads in structural analysis software, generated based on the regional representative pressure value, thus eliminating overly conservative data caused by the superposition of extreme values ​​from different unrelated load conditions.

[0075] In some embodiments, the processor can convert and calculate the regional design wind load of a large-span building by combining the regional representative pressure values ​​of each control area with parameters such as the local wind vibration coefficient, basic wind pressure, and shape coefficient, or by directly assigning the regional representative pressure values ​​as equivalent parameters to the corresponding roof area blocks, and then summarizing and integrating them to determine the regional design wind load of the large-span building.

[0076] In some embodiments, the processor can extract the pressure coefficients of all computational units in each control region under its corresponding key control condition based on the extracted key control conditions and the corresponding control regions; based on the pressure coefficients of all computational units in each control region under its corresponding key control condition, it can calculate the regional representative pressure value of each control region using at least one of the regional maximum pressure coefficient, regional average pressure coefficient, or regional area-weighted pressure coefficient; and use the regional representative pressure value of each control region as the design pressure value of the corresponding region to summarize and determine the regional design wind load of the large-span building, thus completing the determination of the design wind load of the large-span building.

[0077] The pressure coefficient of all computational units in each control area under its corresponding key control condition refers to the set of original grid wind pressure data extracted when finally determining the design wind load for each area, occurring only under the unique key controlled condition corresponding to that area. For example, the pressure coefficient of all computational units in each control area under its corresponding key control condition may include the dimensionless coefficient value of wind pressure distribution under the unique condition of a specific wind direction and a specific combination of open doors and windows, encompassing thousands of grid computational points within a certain northwest corner control area.

[0078] In some embodiments, the processor can read the final mapping table between the control area and the key control condition, use the number of each computing unit in the area and the corresponding key control condition number as joint search conditions, return to access the roof wind pressure database, extract specific pressure coefficient value records that meet the joint conditions, and thus obtain the pressure coefficients of all computing units in each control area under its corresponding key control condition.

[0079] In some embodiments, considering that the results of fluid dynamics calculations are affected by the mesh discretization accuracy and local flow field changes, the boundaries of the initially identified control regions may exhibit a sawtooth distribution or locally isolated discrete regions, which is not conducive to the direct application of engineering design software. Therefore, after determining the regional representative pressure values ​​of each control region, the method further includes a step of optimizing the control regions. Specifically, this may include: First, traversing all control regions, identifying and extracting control regions to be optimized whose areas are lower than a preset area threshold. The preset area threshold can be empirically set based on the overall scale of large-span buildings and the basic force-bearing unit dimensions of structural components. Subsequently, for each control region to be optimized, extracting the surrounding control regions that are spatially adjacent to it, and calculating the difference in regional representative pressure values ​​between the control region to be optimized and the surrounding control regions. When the difference is less than a set merging allowable threshold, the control region to be optimized and its internal calculation units are automatically merged into the surrounding control regions, and its corresponding key control conditions and regional representative pressure values ​​are unified; when the difference is greater than or equal to the merging allowable threshold, the independence of the control region to be optimized is preserved.

[0080] In some embodiments, after merging small-scale regions, continuous geometric correction is performed on the outer boundaries of all control regions. The algorithm smooths jagged boundaries and eliminates local elongated regions, resulting in more regular and smoother control region boundaries. The optimized control regions not only maintain the main wind pressure variation patterns reflected in the fluid dynamics calculations but also meet the requirements of continuous, regular wind pressure zoning and ease of engineering application in structural design.

[0081] In some embodiments, after determining the design wind load of a large-span building and optimizing the control area, the method further includes the step of generating the output results required for structural design. Specifically, based on the regional representative pressure values ​​of each control area and the optimized regional geometric boundaries, load files that can be directly imported into structural analysis software are automatically generated and output. These load files include, but are not limited to, roof wind pressure zoning distribution maps, key control condition distribution maps, and surface load, nodal load, or component load data required for structural stress analysis. This eliminates the tedious work of designers manually dividing wind pressure zones and applying loads point by point, significantly improving engineering application efficiency.

Claims

1. A method for determining wind loads in the design of large-span buildings based on control charts, characterized in that, include: S1: Based on the fluid dynamics calculation results of the large-span building under multiple calculation conditions, obtain the pressure coefficient of each calculation unit of the roof of the large-span building under each calculation condition, and construct a roof wind pressure database; S2: Using the roof wind pressure database, the pressure coefficients of each calculation unit under all calculation conditions are compared to extreme values ​​to determine the target calculation condition that causes the calculation unit to generate the design control pressure. A mapping relationship is established between each calculation unit and its corresponding target calculation condition to construct the roof wind load control map. S3: Based on the roof wind load control map, perform spatial continuity analysis on each calculation unit, and merge calculation units with the same target calculation conditions and pressure difference between adjacent calculation units less than the preset pressure threshold to identify multiple control areas covering the roof. S4: For each control area, statistically analyze the target calculation conditions corresponding to its internal calculation units, establish a mapping relationship between the control area and the target calculation conditions, and extract the key control conditions based on the proportion of the total area of ​​the control area corresponding to each target calculation condition to the total roof area. S5: Based on the extracted key control conditions and corresponding control areas, calculate the regional representative pressure value of each control area to obtain the regional design wind load of the large-span building, and complete the determination of the design wind load of the large-span building.

2. The method for determining wind loads for large-span building design based on control charts according to claim 1, characterized in that, S1 includes: A three-dimensional geometric model is established based on the architectural structure of the large-span building to be analyzed, and calculation conditions including multiple incoming wind directions and various building operating states are determined according to the design wind environment. For each calculation condition, a corresponding fluid dynamics calculation model is established to perform fluid dynamics calculations, and the fluid dynamics calculation results are obtained. The pressure coefficient of each calculation unit of the large-span building roof under each calculation condition is analyzed. The pressure coefficient and the corresponding calculated operating condition information are linked and stored to construct a roof wind pressure database.

3. The method for determining wind loads for large-span building design based on control charts according to claim 1, characterized in that, S2 includes: Using the roof wind pressure database, the pressure coefficients of each calculation unit under all calculation conditions are extracted; The pressure coefficient of each calculation unit under all calculation conditions is compared with the extreme values ​​in turn. The calculation condition that causes the corresponding calculation unit to generate the maximum negative pressure is determined as the target calculation condition, and the number of the target calculation condition is assigned to the corresponding calculation unit. Based on the numbering of all calculation units and their corresponding target calculation conditions, a control matrix covering the roof is established, and the control matrix is ​​used as the roof wind load control map.

4. The method for determining wind loads for large-span building design based on control charts according to claim 1, characterized in that, S3 includes: Based on the roof wind load control map, all calculation units on the roof are traversed, and calculation units with the same target calculation conditions and adjacent spatial locations are selected as candidate regions. The pressure difference between adjacent computing units in the candidate region is compared. When the pressure difference between adjacent computing units is less than the preset pressure threshold, the corresponding computing units are merged. When the pressure difference between adjacent computing units is greater than or equal to the preset pressure threshold, they are divided into different regions to obtain the result of merging adjacent computing units. The merged results of adjacent computing units are identified to obtain multiple control areas that cover the roof and have a unified target computing condition inside.

5. The method for determining wind loads for large-span building design based on control charts according to claim 1, characterized in that, S4 includes: For each control area, the target computing condition number corresponding to its internal computing unit is counted, and a mapping relationship between the control area and the target computing condition is established. Based on the mapping relationship between control regions and target calculation conditions, all control regions corresponding to each target calculation condition are extracted, and the total control area corresponding to each target calculation condition is calculated. Calculate the proportion of the total controlled area to the total roof area corresponding to each target calculation condition, and based on the proportion, eliminate the target calculation conditions that do not meet the preset area proportion conditions and / or the corresponding control areas are discontinuous to obtain the remaining target calculation conditions. The remaining target calculation conditions that meet the preset area ratio conditions and whose corresponding control areas are continuous are used to extract the key control conditions.

6. The method for determining wind loads for large-span building design based on control charts according to claim 1, characterized in that, S5 includes: Based on the extracted key control conditions and corresponding control regions, extract the pressure coefficients of all calculation units in each control region under its corresponding key control conditions. Based on the pressure coefficients of all calculation units in each control area under its corresponding key control conditions, the regional representative pressure value of each control area is obtained by using at least one of the following methods: regional maximum pressure coefficient, regional average pressure coefficient, or regional area weighted pressure coefficient. The regional representative pressure values ​​of each control area are used as the design pressure values ​​of the corresponding areas. The regional design wind loads of large-span buildings are then determined by summarizing these values, thus completing the determination of the design wind loads for large-span buildings.

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