Method, device, equipment and medium for dynamic optimization of parametric modeling of hyperbolic curtain wall

Abstract

The present application provides a method, apparatus, equipment and medium for dynamic optimization of parametric modeling of a hyperbolic curtain wall. The method comprises obtaining a construction plan of the hyperbolic curtain wall to be optimized, environmental information of the hyperbolic curtain wall setting and a surface design target corresponding to the hyperbolic curtain wall model; constructing a preliminary external profile corresponding to the hyperbolic curtain wall based on the environmental information, the surface design target and the construction plan; parsing the construction plan to obtain multiple component types and component parameters and component positions corresponding to each component type; constructing a finite element simulation model based on the environmental information, the construction plan, the component parameters and the component positions, and optimizing the component according to the surface design target; dynamically optimizing the component parameters and component positions corresponding to each component type in the finite element simulation model based on the optimization objective function and the preliminary external profile, outputting the optimized component parameters and component positions corresponding to each component type, and completing the avoidance design of multiple components in the hyperbolic curtain wall.

Description

Technical Field

[0001] The present application relates to the field of parameter optimization technology, and in particular to a method, device, equipment and medium for dynamic optimization of parametric modeling of hyperbolic curtain walls. Background Art

[0002] With the continuous advancement of modern architectural aesthetics and engineering technology, hyperbolic curtain walls have been widely used in high-end projects such as large public buildings and commercial complexes due to their unique visual effects and structural properties. However, the design and construction of hyperbolic curtain walls face numerous challenges, particularly the issue of avoidance design in complex environments. Traditional design methods often rely on experienced engineers to manually adjust parameters, which is not only time-consuming and labor-intensive but also difficult to guarantee the optimal final design. Especially when considering multiple factors, how to achieve an aesthetically pleasing and cost-effective solution while meeting functional requirements has become a pressing issue. Summary of the Invention

[0003] This application provides a method, device, equipment, and medium for dynamic optimization of parametric modeling of hyperbolic curtain walls. This approach aims to address the challenges of traditional design methods, which often rely on experienced engineers manually adjusting parameters. This is not only time-consuming and labor-intensive, but also difficult to guarantee the optimality of the final design. Especially when multiple factors need to be considered, achieving an aesthetically pleasing, cost-effective solution while meeting functional requirements becomes a pressing issue.

[0004] In a first aspect, the present application provides a method for dynamic optimization of parametric modeling of a hyperbolic curtain wall, comprising:

[0005] Obtaining a construction plan of the hyperbolic curtain wall to be optimized, environmental information of the hyperbolic curtain wall setting, and a surface design target corresponding to the hyperbolic curtain wall model;

[0006] Constructing a preliminary outline corresponding to the hyperbolic curtain wall according to the environmental information, the curved surface design target and the construction plan;

[0007] Parsing the construction plan to obtain multiple component types and component parameters and component positions corresponding to each component type;

[0008] Constructing a finite element simulation model based on the environmental information, construction plan, component parameters and component positions, and optimizing an objective function based on the surface design target component;

[0009] According to the optimization objective function and the preliminary shape contour, the component parameters and component positions corresponding to each component type in the finite element simulation model are dynamically optimized, and the optimized component parameters and component positions corresponding to each component type are output to complete the avoidance design of multiple components in the hyperbolic curtain wall.

[0010] In some embodiments, constructing a preliminary outer contour corresponding to the hyperbolic curtain wall based on the environmental information, the curved surface design target, and the construction plan includes: performing image recognition on the construction plan and converting it into a preset document format; obtaining constraint parameters corresponding to the hyperbolic curtain wall based on the curved surface design target, the constraint parameters including at least a minimum bending radius and a maximum allowable deviation; calculating preliminary contour parameters corresponding to the hyperbolic curtain wall based on the constraint parameters, the construction plan in a preset document format, and the environmental information; and constructing the preliminary outer contour corresponding to the hyperbolic curtain wall based on the preliminary contour parameters.

[0011] Exemplarily, the calculating of preliminary contour parameters corresponding to the hyperbolic curtain wall according to the constraint parameters, the construction plan in a preset document format, and the environmental information includes: obtaining a construction plan gradient tensor corresponding to the construction plan; constructing an environmental factor matrix and an environmental sensitivity coefficient according to the environmental information; the environmental factor matrix includes at least a wind load coefficient, a temperature gradient, a snow load density, and a seismic coefficient; calculating a constraint balance factor according to the maximum allowable deviation and the minimum bending radius based on a softmax function; and calculating a contour parameter matrix corresponding to the preliminary outer contour according to the constraint balance factor, the construction plan gradient tensor, the environmental factor matrix, the environmental sensitivity coefficient, the maximum allowable deviation, and the minimum bending radius.

[0012] It should be noted that, in some embodiments, the expression of the profile parameter matrix includes:

[0013] ;

[0014] in, is the profile parameter matrix, is the minimum bending radius, is the maximum allowable deviation, is the gradient tensor of the construction plane, is the construction plan coordinate matrix, is the environmental factor matrix, is the environmental sensitivity coefficient, is the constraint balance factor, is a dynamic activation function.

[0015] In some embodiments, optimizing the objective function according to the curved surface design target component includes: constructing a geometric conformality constraint corresponding to the hyperbolic curtain wall according to the curved surface design target; and constructing the optimization objective function according to the geometric conformality constraint; wherein the expression of the geometric conformality constraint includes:

[0016] ;

[0017] in, is the geometric conformality constraint, is the surface parameterization matrix of the construction plan, is the discretization matrix of the target surface corresponding to the hyperbolic curtain wall, is the adaptive weight, is the target Gaussian curvature distribution, is the curvature sensitive weight, is the surface gradient operator, which is used to calculate the first-order geometric change rate of the surface. is the Frobenius norm, which measures the overall deviation of the gradient field, is the Gaussian curvature, represents the surface corresponding to the hyperbolic curtain wall, express The area of the infinitesimal element on .

[0018] Exemplarily, before optimizing the objective function according to the curved surface design target component, the method further includes: constructing structural performance constraints, manufacturing constraints, and avoidance constraints corresponding to the hyperbolic curtain wall according to the curved surface design target; constructing environmental constraints according to the environmental information, so as to construct the optimization objective function according to the geometric conformality constraints, structural performance constraints, manufacturing constraints, avoidance constraints, and environmental constraints.

[0019] In some embodiments, the dynamic optimization of component parameters and component positions corresponding to each component type in the finite element simulation model according to the optimization objective function and the preliminary shape contour includes: performing orthogonal decomposition and dimensionality reduction on the component parameters and component positions; setting an iterative format corresponding to the optimization of the component parameters and component positions; determining a convergence condition according to the surface design objective; completing the configuration of the dynamic optimization solver according to the iterative format and convergence condition; and dynamically optimizing the component parameters and component positions corresponding to each component type in the finite element simulation model under the configured solver according to the optimization objective function and the preliminary shape contour.

[0020] In a second aspect, the present application provides a hyperbolic curtain wall parametric modeling dynamic optimization device, comprising:

[0021] A target acquisition module is used to obtain the construction plan of the hyperbolic curtain wall to be optimized, the environmental information of the hyperbolic curtain wall setting, and the surface design target corresponding to the hyperbolic curtain wall model;

[0022] A contour construction module, configured to construct a preliminary outer contour corresponding to the hyperbolic curtain wall according to the environmental information, the curved surface design target and the construction plan;

[0023] A plane parsing module, configured to parse the construction plan to obtain a plurality of component types and component parameters and component positions corresponding to each component type;

[0024] An environment construction module is used to construct a finite element simulation model based on the environment information, construction plan, component parameters and component positions, and optimize the objective function of the target component according to the surface design;

[0025] The avoidance completion module is used to dynamically optimize the component parameters and component positions corresponding to each component type in the finite element simulation model according to the optimization objective function and the preliminary shape contour, output the optimized component parameters and component positions corresponding to each component type, and complete the avoidance design of multiple components in the hyperbolic curtain wall.

[0026] In a third aspect, the present application provides a computer device comprising a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and implement the method provided in any embodiment of the present application when executing the computer program.

[0027] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer-readable instructions are executed by the processor, one or more processors execute the method provided in any embodiment of the present application.

[0028] The present application provides a method, apparatus, device, and medium for dynamic optimization of parametric modeling of hyperbolic curtain walls. This process involves collecting detailed construction plans, including the building's overall layout, dimensions, and structural details. Environmental information about the project site, such as climate conditions (temperature, humidity, wind speed, etc.), lighting conditions, and geographic location, is collected. Design objectives for the hyperbolic curtain wall are clarified, including specific requirements for aesthetics, functionality, and cost-effectiveness. Using parametric design software (such as Rhino or Grasshopper), a preliminary hyperbolic curtain wall outline is generated based on the construction plans and environmental information. This stage focuses on macro-level design, ensuring that the basic framework meets functional requirements and lays the foundation for subsequent refinement. The generated preliminary model is initially evaluated to ensure that its geometry conforms to the design intent and is physically feasible. The various components that make up the hyperbolic curtain wall, such as glass panels, steel frames, and connectors, are analyzed from the construction plans. Specific parameters for each component, including dimensions, material, and thickness, are extracted. The relative positions of each component within the structure are recorded for subsequent finite element analysis. Based on the information collected above, a comprehensive finite element simulation model is constructed using finite element analysis software (such as ANSYS or Abaqus). This model not only considers physical property constraints but also incorporates aesthetic considerations. Based on the surface design objectives, an optimization objective function is defined. The optimization objective can be diverse, such as minimizing material cost, maximizing structural stability, or optimizing lighting effects. An optimization algorithm (such as a genetic algorithm or particle swarm optimization) is used to solve the objective function, automatically adjusting the specific parameter values and spatial configuration of each component. This process is dynamic, with the algorithm iteratively trying new combinations until it finds the optimal design that best meets all pre-defined conditions. During each iteration, the optimization results are checked to see if they have converged to the global optimal solution. If convergence conditions are met, the iteration is terminated; otherwise, the optimization continues. Ultimately, the system outputs the exact parameter values and precise placement of each optimized component, completing the entire avoidance design process. A detailed optimization report is generated, including a comparison before and after optimization and evaluation of various indicators, for designers and engineers to reference.

[0029] Consider a large public building project located in a coastal city. Its exterior is planned to feature a streamlined, hyperbolic glass curtain wall to enhance visual appeal and increase natural lighting efficiency. Using this method, the following steps can be followed: Collect meteorological data for the project site, such as average annual temperature, humidity, and wind speed. Obtain a sun exposure distribution map to understand the lighting conditions during different seasons and time periods. Obtain detailed construction plans and a description of the design intent from the architect. Use Rhino and Grasshopper to create a 3D conceptual model that reflects the architect's creative intent. Conduct a preliminary evaluation of the preliminary model to ensure that it geometrically meets the design intent and is physically feasible. Extract all involved materials (e.g., steel frame, laminated glass panels), along with their intended installation coordinates, from the detailed construction blueprints. Record the specific parameters of each component, such as length, width, and thickness. Develop a complex FEM model in ANSYS, incorporating multiple criteria, including static stability analysis and thermal performance evaluation. Define optimization objectives based on the design goals, such as minimizing material cost, maximizing structural stability, and optimizing lighting. Run the optimization program, allowing the computer to automatically explore the optimal structural form and material selection options. Using genetic algorithms or particle swarm optimization, iteratively adjusts the parameter values and positions of each component until the optimal solution is found. Once completed, designers can directly develop detailed construction instructions based on the software's recommendations. A detailed optimization report is generated, including a comparison of the before and after results and evaluation of various indicators.

[0030] Compared with traditional manual adjustments, this method significantly shortens the design cycle and reduces labor costs. Automated tools allow designers to complete complex calculations and adjustments more quickly, improving overall work efficiency. Supported by rigorous scientific mathematical models, the final results are more reliable and stable, reducing the risk of rework due to human error. Optimization algorithms find the global optimal solution, ensuring the design achieves optimal results in all aspects. This encourages the exploration of more novel and unique architectural styles, helping to advance the field of architectural design. Parametric design and optimization methods make it easier for designers to experiment with different design options, inspiring more innovative ideas. Optimizing resources and reducing unnecessary waste promotes the implementation of green and sustainable urban development. By optimizing material usage and structural design, the overall project cost can be significantly reduced while minimizing environmental impact. This method not only considers structural safety and stability, but also aesthetics and cost-effectiveness, achieving comprehensive optimization of multiple factors. This ensures that the final design better meets the needs of both the client and the user.

[0031] In summary, the proposed dynamic optimization method for parametric modeling of hyperbolic curtain walls can significantly improve the quality and efficiency of design while reducing costs and resource consumption by combining advanced computer-aided design and finite element analysis technology. It is a modern design method with great application prospects.

[0032] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0034] Figure 1 This is a schematic flow chart of the steps of a dynamic optimization method for parametric modeling of a hyperbolic curtain wall provided in one embodiment of the present application;

[0035] Figure 2 This is a schematic block diagram of the structure of a device for dynamic optimization of parametric modeling of a hyperbolic curtain wall provided in one embodiment of the present application;

[0036] Figure 3 This is a schematic block diagram of the structure of a computer device provided in one embodiment of the present application.

[0037] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0039] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.

[0040] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish between identical or similar items having substantially the same functions and effects. Those skilled in the art will understand that terms such as "first" and "second" do not limit the quantity or order of execution, and that terms such as "first" and "second" do not necessarily define differences.

[0041] It should be understood that the terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0042] It will also be understood that the term "and / or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0043] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features therein may be combined with each other.

[0044] With the continuous advancement of modern architectural aesthetics and engineering technology, hyperbolic curtain walls have been widely used in high-end projects such as large public buildings and commercial complexes due to their unique visual effects and structural properties. However, the design and construction of hyperbolic curtain walls face numerous challenges, particularly the issue of avoidance design in complex environments. Traditional design methods often rely on experienced engineers to manually adjust parameters, which is not only time-consuming and labor-intensive but also difficult to guarantee the optimal final design. Especially when considering multiple factors, how to achieve an aesthetically pleasing and cost-effective solution while meeting functional requirements has become a pressing issue.

[0045] To resolve the above issues, please refer to Figure 1 ,like Figure 1 As shown, the provided hyperbolic curtain wall parametric modeling dynamic optimization method includes steps S101 to S105. The details are as follows:

[0046] Step S101: Obtain a construction plan of a hyperbolic curtain wall to be optimized, environmental information of the hyperbolic curtain wall setting, and a curved surface design target corresponding to the hyperbolic curtain wall model.

[0047] Specifically, this involves gathering all necessary information about the PV module to be designed or optimized, including but not limited to the specific conditions of the installation environment (such as light intensity and temperature fluctuations) and the user's requirements for the module's form and functionality. Data can be collected through on-site visits and customer interviews, and specialized software tools can be used to simulate the performance of PV modules under different environmental conditions. For example, if the goal is to install a PV module that can serve as both a partition wall and a power source in a semi-open office space, a detailed understanding of factors such as the space's sunlight patterns and the temperature difference between indoor and outdoor areas is essential. This ensures that the design is more closely aligned with the actual application scenario, enhancing the practicality of the final product.

[0048] Construction plans are typically completed by the architectural design team during the project design phase. These plans can be extracted from Building Information Modeling (BIM) systems, which integrate various aspects of the building, including the curtain wall's layout and dimensioning. For example, for a large commercial complex's hyperbolic curtain wall project, the design team created a detailed BIM model using Revit software. By exporting the model in a specific format (such as DWG or DXF), they were able to obtain the construction plans for the hyperbolic curtain wall. The plans clearly indicate the curtain wall's boundaries, door and window locations, and connection points with other building structures. Environmental information includes geographic environment and meteorological conditions. Geographical environment information, such as the topography of the project site and the distribution of surrounding buildings, can be obtained through a geographic information system (GIS). Meteorological information, including wind speed, direction, sunshine duration, and temperature range, can be obtained from the local meteorological department. For example, consider a hyperbolic curtain wall building in a coastal city. GIS data reveals the surrounding high-rise buildings, which could affect ventilation and lighting. Meteorological data also indicates that the prevailing wind direction in the area is southeasterly year-round, with frequent summer rainstorms. This information is crucial for subsequent curtain wall design. Architects typically determine the design objectives for curved surfaces based on the building's overall style and functional requirements. For example, designers may desire a smooth, curved shape to complement the building's modern aesthetic, or require the curtain wall to create unique light and shadow effects from varying viewing angles. These design objectives can be provided to the optimization team in the form of text descriptions, renderings, or 3D models.

[0049] Step S102: Constructing a preliminary outline corresponding to the hyperbolic curtain wall according to the environmental information, the curved surface design target and the construction plan.

[0050] Specifically, based on the information gathered in the previous step, begin drafting the basic shape and layout of the photovoltaic panels. Use CAD or other 3D modeling software for preliminary design; this application does not restrict the type of 3D software used. Design a modular photovoltaic panel that can be freely combined into various sizes and shapes, allowing for both decorative wall decoration and efficient power generation. This lays the foundation for subsequent precise adjustments and facilitates rapid design iteration.

[0051] Based on the acquired information on geographical environment and meteorological conditions, make preliminary adjustments to the preliminary outline of the hyperbolic curtain wall. For example, if the dominant wind direction at the project site is southeast, in order to reduce the impact of wind load on the curtain wall, the southeast side of the curtain wall can be designed to be flatter to reduce wind resistance. At the same time, taking into account the obstruction of surrounding buildings, adjust the height and inclination angle of the curtain wall to ensure sufficient indoor lighting. Use computer-aided design (CAD) software to construct the preliminary outline of the hyperbolic curtain wall according to the surface design goals. For example, use the surface modeling tool in Rhino software, combined with the renderings or three-dimensional models provided by the designer, to create a hyperbolic surface that meets the design requirements. During the modeling process, different surface effects can be achieved by adjusting the position of the control points and the curvature of the curve. Match the preliminarily constructed hyperbolic surface with the construction plan to ensure that the boundaries of the curtain wall, the positions of doors and windows, etc. are consistent with the plane. Figure 1 You can use the alignment and scaling features in your CAD software to accurately place the surface model on the plan view.

[0052] Step S103: Analyze the construction plan to obtain multiple component types and component parameters and component positions corresponding to each component type.

[0053] Specifically, we conducted an in-depth analysis of existing design drawings to identify key dimensions and other important properties of each component. We also employed BIM (Building Information Modeling) and other technologies to digitize the design files. We determined the optimal aspect ratio, thickness, and other physical characteristics of each photovoltaic panel. This facilitated subsequent calculations and analysis, ensuring coordination between components.

[0054] Image processing and pattern recognition techniques are used to analyze the construction plan and identify different types of components. For example, common hyperbolic curtain wall components include glass panels, aluminum alloy frames, and connectors. By analyzing the color, line style, and dimensions of different graphics in the plan, various component types can be accurately identified. For each component type, corresponding parameters are extracted from the construction plan. For example, for glass panels, parameters such as size, thickness, and color are required; for aluminum alloy frames, parameters such as cross-sectional shape, dimensions, and material are required. These parameters can be obtained by measuring the dimensions of the graphics in the plan and consulting relevant design documentation. The position of each component is determined based on the coordinate system in the construction plan. The coordinates of the component's center point or corner point in the plan can be read to determine its position on the plane. Simultaneously, the component's position in three-dimensional space is determined based on the preliminary outline of the hyperbolic curtain wall.

[0055] Step S104: Construct a finite element simulation model based on the environmental information, construction plan, component parameters and component positions, and optimize the objective function of the target component according to the surface design.

[0056] Specifically, based on the results of the previous steps, a mathematical model was created that encompassed all relevant factors, and a performance optimization objective function was set. Finite element analysis (FEA) software was then used to conduct virtual testing. The goal was to maximize the total power generation of the entire system within a specific time period while minimizing material costs. This enabled potential issues to be identified and addressed before actual manufacturing, saving time and resources.

[0057] Using finite element analysis software (such as ANSYS or ABAQUS), a finite element simulation model of the hyperbolic curtain wall is constructed based on environmental information, construction plans, component parameters, and component locations. First, the preliminary outline of the hyperbolic curtain wall and component information are imported into the finite element software to establish the geometric model. Then, based on the component material properties and connection methods, the element type and material properties are defined, and the model is meshed. Finally, based on the environmental information, appropriate boundary conditions and loads, such as wind speed and temperature variations, are applied. Based on the surface design objectives, an optimization objective function is constructed. This optimization objective function is typically a multi-objective function that considers multiple factors, such as the curtain wall's aesthetics, structural safety, and economic efficiency. For example, the objective function can be defined as a weighted sum of minimizing the curtain wall's wind load response, maximizing the curtain wall's daylighting area, and minimizing the curtain wall's construction cost. The specific weightings can be adjusted based on the actual project requirements.

[0058] Step S105. Dynamically optimize the component parameters and component positions corresponding to each component type in the finite element simulation model according to the optimization objective function and the preliminary shape contour, output the optimized component parameters and component positions corresponding to each component type, and complete the avoidance design of multiple components in the hyperbolic curtain wall.

[0059] Specifically, the model continuously adjusts variable values based on a pre-defined objective function until the optimal solution is found. Intelligent optimization algorithms such as genetic algorithms and particle swarm optimization are used to automatically find the optimal configuration. By repeatedly testing different photovoltaic panel permutations and combinations, a solution is found that meets both aesthetic requirements and maximizes efficiency. The resulting product is both aesthetically pleasing and provides superior performance, meeting the diverse needs of users.

[0060] Select appropriate dynamic optimization algorithms, such as genetic algorithms and particle swarm optimization algorithms, to optimize component parameters and positions in the finite element simulation model. These algorithms possess global search capabilities and can find the optimal solution within a large parameter space. The selected optimization algorithm takes the optimization objective function and the finite element simulation model as input and performs iterative calculations. In each iteration, the algorithm calculates the value of the objective function based on the current component parameters and positions, and adjusts the parameters and positions according to specific rules to gradually approach the optimal solution. Simultaneously, the finite element simulation model is used to analyze and evaluate the performance of each adjusted solution. When the optimization algorithm meets convergence criteria (e.g., the objective function value remains unchanged or changes within a certain threshold), the optimized component parameters and positions for each component type are output. This parameter and position information can be used to guide the construction and installation of hyperbolic curtain walls, enabling the avoidance design of multiple components, ensuring that the curtain wall meets functional requirements while achieving an aesthetically pleasing and cost-effective solution.

[0061] Through the specific implementation of the above steps, the avoidance design problem of hyperbolic curtain walls in complex environments can be effectively solved, and the design efficiency and quality can be improved.

[0062] This embodiment of the present application provides a method for dynamic optimization of parametric modeling of hyperbolic curtain walls. This method involves collecting detailed construction plans, including the building's overall layout, dimensions, and structural details. Environmental information about the project site, such as climate conditions (temperature, humidity, wind speed, etc.), lighting conditions, and geographic location, is also collected. Design objectives for the hyperbolic curtain wall are clarified, including specific requirements for aesthetics, functionality, and cost-effectiveness. Using parametric design software (such as Rhino or Grasshopper), a preliminary hyperbolic curtain wall outline is generated based on the construction plans and environmental information. This stage focuses on macro-level design, ensuring that the basic framework meets functional requirements and lays the foundation for subsequent refinement. The generated preliminary model is initially evaluated to ensure that its geometry conforms to the design intent and is physically feasible. The various components that make up the hyperbolic curtain wall, such as glass panels, steel frames, and connectors, are analyzed from the construction plans. Specific parameters for each component, including dimensions, material, and thickness, are extracted. The relative positions of each component within the structure are recorded for subsequent finite element analysis. Based on the information collected above, a comprehensive finite element simulation model is constructed using finite element analysis software (such as ANSYS or Abaqus). This model not only considers physical property constraints but also incorporates aesthetic considerations. Based on the surface design objectives, an optimization objective function is defined. The optimization objective can be diverse, such as minimizing material cost, maximizing structural stability, or optimizing lighting effects. An optimization algorithm (such as a genetic algorithm or particle swarm optimization) is used to solve the objective function, automatically adjusting the specific parameter values and spatial configuration of each component. This process is dynamic, with the algorithm iteratively trying new combinations until it finds the optimal design that best meets all pre-defined conditions. During each iteration, the optimization results are checked to see if they have converged to the global optimal solution. If convergence conditions are met, the iteration is terminated; otherwise, the optimization continues. Ultimately, the system outputs the exact parameter values and precise placement of each optimized component, completing the entire avoidance design process. A detailed optimization report is generated, including a comparison before and after optimization and evaluation of various indicators, for designers and engineers to reference.

[0063] Consider a large public building project located in a coastal city. Its exterior is planned to feature a streamlined, hyperbolic glass curtain wall to enhance visual appeal and increase natural lighting efficiency. Using this method, the following steps can be followed: Collect meteorological data for the project site, such as average annual temperature, humidity, and wind speed. Obtain a sun exposure distribution map to understand the lighting conditions during different seasons and time periods. Obtain detailed construction plans and a description of the design intent from the architect. Use Rhino and Grasshopper to create a 3D conceptual model that reflects the architect's creative intent. Conduct a preliminary evaluation of the preliminary model to ensure that it geometrically meets the design intent and is physically feasible. Extract all involved materials (e.g., steel frame, laminated glass panels), along with their intended installation coordinates, from the detailed construction blueprints. Record the specific parameters of each component, such as length, width, and thickness. Develop a complex FEM model in ANSYS, incorporating multiple criteria, including static stability analysis and thermal performance evaluation. Define optimization objectives based on the design goals, such as minimizing material cost, maximizing structural stability, and optimizing lighting. Run the optimization program, allowing the computer to automatically explore the optimal structural form and material selection options. Using genetic algorithms or particle swarm optimization, iteratively adjusts the parameter values and positions of each component until the optimal solution is found. Once completed, designers can directly develop detailed construction instructions based on the software's recommendations. A detailed optimization report is generated, including a comparison of the before and after results and evaluation of various indicators.

[0064] Compared with traditional manual adjustments, this method significantly shortens the design cycle and reduces labor costs. Automated tools allow designers to complete complex calculations and adjustments more quickly, improving overall work efficiency. Supported by rigorous scientific mathematical models, the final results are more reliable and stable, reducing the risk of rework due to human error. Optimization algorithms find the global optimal solution, ensuring the design achieves optimal results in all aspects. This encourages the exploration of more novel and unique architectural styles, helping to advance the field of architectural design. Parametric design and optimization methods make it easier for designers to experiment with different design options, inspiring more innovative ideas. Optimizing resources and reducing unnecessary waste promotes the implementation of green and sustainable urban development. By optimizing material usage and structural design, the overall project cost can be significantly reduced while minimizing environmental impact. This method not only considers structural safety and stability, but also aesthetics and cost-effectiveness, achieving comprehensive optimization of multiple factors. This ensures that the final design better meets the needs of both the client and the user.

[0065] In summary, the proposed dynamic optimization method for parametric modeling of hyperbolic curtain walls can significantly improve the quality and efficiency of design while reducing costs and resource consumption by combining advanced computer-aided design and finite element analysis technology. It is a modern design method with great application prospects.

[0066] In some embodiments, constructing a preliminary outer contour corresponding to the hyperbolic curtain wall based on the environmental information, the curved surface design target, and the construction plan includes: performing image recognition on the construction plan and converting it into a preset document format; obtaining constraint parameters corresponding to the hyperbolic curtain wall based on the curved surface design target, the constraint parameters including at least a minimum bending radius and a maximum allowable deviation; calculating preliminary contour parameters corresponding to the hyperbolic curtain wall based on the constraint parameters, the construction plan in a preset document format, and the environmental information; and constructing the preliminary outer contour corresponding to the hyperbolic curtain wall based on the preliminary contour parameters.

[0067] The preliminary outline of the hyperbolic curtain wall is constructed based on environmental information, surface design objectives, and construction plans. The specific steps include: performing image recognition on the construction plan and converting it into a preset document format. Obtaining the constraint parameters of the hyperbolic curtain wall, such as the minimum bend radius and maximum allowable deviation, based on the surface design objectives. Based on the constraint parameters, the construction plan in the preset document format, and environmental information, preliminary outline parameters of the hyperbolic curtain wall are calculated. The preliminary outline of the hyperbolic curtain wall is constructed based on these preliminary outline parameters.

[0068] Use image processing tools (such as OpenCV) to perform image recognition on the construction plan and extract key geometric information. Convert the recognized data into a pre-set document format (such as DXF or SVG) for subsequent processing. For example, open the construction plan image file. Use the edge detection tools in the image processing software to extract lines and boundaries from the image. Convert the extracted lines and boundaries into a vector graphics format (such as DXF or SVG) for subsequent calculations and modeling. Save the converted file, ensuring that it is formatted correctly and contains all necessary details. Determine the minimum bend radius and maximum allowable deviation for the hyperbolic curtain wall based on design specifications and user requirements. For example, the minimum bend radius may be 500mm, with a maximum allowable deviation of ±5mm. Determine the materials used and their physical properties, especially the minimum bend radius. Determine the maximum allowable deviation based on project requirements and industry standards. Record these parameters for use in subsequent calculations.

[0069] Numerical analysis methods are used to calculate the gradient tensor of the construction plan, reflecting the plan's changing trends. The environmental factor matrix includes factors such as wind load coefficients, temperature gradients, snow load density, and seismic coefficients. Environmental sensitivity coefficients are used to quantify the impact of these environmental factors on the design. The coordinate data of the construction plan is read from a converted preset document format. Numerical differentiation methods are used to calculate the gradient tensor of the construction plan. The gradient tensor represents the direction and slope of each point. The gradient tensor data is recorded for subsequent calculations.

[0070] Based on the softmax function, the constraint balance factor is calculated by combining the maximum allowable deviation and the minimum bending radius. The contour parameter matrix corresponding to the preliminary outline is calculated by comprehensively considering the constraint balance factor, the construction plan gradient tensor, the environmental factor matrix, the environmental sensitivity coefficient, the maximum allowable deviation, and the minimum bending radius. Using the calculated contour parameter matrix, the preliminary outline of the hyperbolic curtain wall is constructed in 3D modeling software. For example, parametric modeling can be performed using Rhinoceros + Grasshopper. Environmental factor data, such as wind load, temperature gradient, snow load, and seismic coefficient, is collected and organized into a matrix. An environmental sensitivity coefficient is assigned to indicate the degree of impact of the environmental factor on the design. The environmental factor matrix and environmental sensitivity coefficient are recorded for subsequent calculations. A new project is created in the 3D modeling software. The calculated contour parameter matrix is imported. Using parametric modeling tools, a 3D model is generated based on the contour parameter matrix. Model details are adjusted to ensure that it meets design requirements. The model file is saved for subsequent optimization and verification.

[0071] Exemplarily, the calculating of preliminary contour parameters corresponding to the hyperbolic curtain wall according to the constraint parameters, the construction plan in a preset document format, and the environmental information includes: obtaining a construction plan gradient tensor corresponding to the construction plan; constructing an environmental factor matrix and an environmental sensitivity coefficient according to the environmental information; the environmental factor matrix includes at least a wind load coefficient, a temperature gradient, a snow load density, and a seismic coefficient; calculating a constraint balance factor according to the maximum allowable deviation and the minimum bending radius based on a softmax function; and calculating a contour parameter matrix corresponding to the preliminary outer contour according to the constraint balance factor, the construction plan gradient tensor, the environmental factor matrix, the environmental sensitivity coefficient, the maximum allowable deviation, and the minimum bending radius.

[0072] This example details how to calculate preliminary contour parameters based on constraint parameters, a construction plan in a pre-set document format, and environmental information. The steps include: obtaining the construction plan gradient tensor; constructing the environmental factor matrix and environmental sensitivity coefficients; calculating the constraint balance factor using a softmax function; and calculating the contour parameter matrix corresponding to the preliminary outline.

[0073] By reading the coordinate data of the construction plan from the converted preset document format. Use the numerical differentiation method to calculate the gradient tensor of the construction plan. The gradient tensor represents the direction and slope of each point. Record the gradient tensor data for subsequent calculations. Collect environmental factor data such as wind load, temperature gradient, snow load, and seismic coefficient. Organize these environmental factors into a matrix. Set the environmental sensitivity coefficient. Record the environmental factor matrix and environmental sensitivity coefficient for subsequent calculations. Define the input vector, which includes the maximum allowable deviation and the minimum bending radius. Use the softmax function to calculate the constraint balance factor. The softmax function converts the input vector into a probability distribution to obtain the balance factor. Record the constraint balance factor for subsequent calculations.

[0074] It should be noted that, in some embodiments, the expression of the profile parameter matrix includes:

[0075] ;

[0076] in, is the profile parameter matrix, is the minimum bending radius, is the maximum allowable deviation, is the gradient tensor of the construction plane, is the construction plan coordinate matrix, is the environmental factor matrix, is the environmental sensitivity coefficient, is the constraint balance factor, is a dynamic activation function.

[0077] By comprehensively considering multiple factors, the preliminary design of the exterior contour is ensured to be more accurate and reasonable. Incorporating environmental factors and constraints ensures greater stability and durability in practical applications. Potential problems are identified and resolved early, reducing the cost of later modifications and rework. This allows the design to better adapt to varying environmental conditions, improving the reliability and efficiency of the overall system. For example, numerical differentiation methods are used to calculate the gradient tensor of the construction plan.

[0078] In some embodiments, optimizing the objective function according to the curved surface design target component includes: constructing a geometric conformality constraint corresponding to the hyperbolic curtain wall according to the curved surface design target; and constructing the optimization objective function according to the geometric conformality constraint; wherein the expression of the geometric conformality constraint includes:

[0079] ;

[0080] in, is the geometric conformality constraint, is the surface parameterization matrix of the construction plan, is the discretization matrix of the target surface corresponding to the hyperbolic curtain wall, is the adaptive weight, is the target Gaussian curvature distribution, is the curvature sensitive weight, is the surface gradient operator, which is used to calculate the first-order geometric change rate of the surface. is the Frobenius norm, which measures the overall deviation of the gradient field, is the Gaussian curvature, represents the surface corresponding to the hyperbolic curtain wall, express The area of the infinitesimal element on .

[0081] By coupling multiple constraints, an optimization objective function is constructed to ensure that the curtain wall design simultaneously meets geometric conformality, structural performance, manufacturing feasibility, and avoidance requirements. The specific steps include: Constructing geometric conformality constraints based on the surface design objectives. Constructing an optimization objective function based on these and other constraints. In addition to geometric conformality constraints, structural performance constraints, manufacturing constraints, avoidance constraints, and environmental constraints also need to be considered. The specific form and weight of each constraint should be determined based on the actual situation.

[0082] Exemplarily, before optimizing the objective function according to the curved surface design target component, the method further includes: constructing structural performance constraints, manufacturing constraints, and avoidance constraints corresponding to the hyperbolic curtain wall according to the curved surface design target; constructing environmental constraints according to the environmental information, so as to construct the optimization objective function according to the geometric conformality constraints, structural performance constraints, manufacturing constraints, avoidance constraints, and environmental constraints.

[0083] Geometric conformality constraints can be constructed by determining the target surface and Gaussian curvature distribution based on the design objectives to calculate the geometric conformality constraints. Structural performance constraints consider mechanical requirements such as wind loads and snow loads. Manufacturing constraints consider machining accuracy and equipment limitations. Avoidance constraints consider spatial constraints such as pipeline crossings. Environmental constraints consider factors such as temperature changes and sunlight.

[0084] By comprehensively considering multiple constraints, we achieve more comprehensive design optimization, ensuring that the design is optimal in terms of geometry, structural performance, manufacturing feasibility, and environmental adaptability. This single optimization process reduces the time and cost of multiple design iterations.

[0085] In some embodiments, the dynamic optimization of component parameters and component positions corresponding to each component type in the finite element simulation model according to the optimization objective function and the preliminary shape contour includes: performing orthogonal decomposition and dimensionality reduction on the component parameters and component positions; setting an iterative format corresponding to the optimization of the component parameters and component positions; determining a convergence condition according to the surface design objective; completing the configuration of the dynamic optimization solver according to the iterative format and convergence condition; and dynamically optimizing the component parameters and component positions corresponding to each component type in the finite element simulation model under the configured solver according to the optimization objective function and the preliminary shape contour.

[0086] Efficient dynamic optimization of component parameters is achieved through orthogonal decomposition and dimensionality reduction and intelligent optimization algorithms. The specific steps include: Orthogonal decomposition and dimensionality reduction: Perform orthogonal decomposition and dimensionality reduction on component parameters and positions. Set the iteration format: Set the iteration format for optimizing component parameters and positions. Determine the convergence criteria: Determine the convergence criteria based on the surface design objectives. Configure the solver: Complete the solver configuration based on the iteration format and convergence criteria. Dynamic optimization: Dynamically optimize the component parameters and positions in the finite element simulation model using the configured solver.

[0087] Use methods such as principal component analysis (PCA) to map high-dimensional parameters into a low-dimensional orthogonal space, reducing optimization complexity. Select an appropriate optimization algorithm, such as a genetic algorithm (GA) or particle swarm optimization (PSO). Set parameters such as the iteration step size and maximum number of iterations. Set convergence conditions based on the design goals, such as requiring the objective function change to be less than a certain threshold or reaching the maximum number of iterations. Configure the solver based on the selected optimization algorithm and convergence conditions, such as setting the initial population, crossover probability, and mutation probability. Using this configured solver, dynamically optimize component parameters and positions in the finite element simulation model.

[0088] Orthogonal decomposition dimensionality reduction: Use PCA to map high-dimensional parameters to a low-dimensional space, preserving the main features. For example, 50 design variables can be reduced to 8 principal components.

[0089] Set the iteration format: Select the Particle Swarm Optimization (PSO) algorithm. Set the initial population size to 50 and the maximum number of iterations to 200.

[0090] Convergence conditions are determined: the objective function changes by less than 1e-5 or the maximum number of iterations is reached.

[0091] Configure the solver: initialize the population, set the inertia weight to 0.729, the individual learning factor to 1.49445, and the social learning factor to 1.49445.

[0092] Under the configured solver, component parameters and positions in the finite element simulation model are dynamically optimized.

[0093] Assume that the initial design variables of a project are 50, and after PCA dimensionality reduction, 8 principal components are retained.

[0094] Set the PSO algorithm parameters: Initial population size: 50. Maximum number of iterations: 200. Inertia weight: 0.729. Individual learning factor: 1.49445. Social learning factor: 1.49445. Convergence criteria: Objective function change less than 1e-5 or the maximum number of iterations reached. Using the configured solver, dynamically optimize component parameters and positions in the finite element simulation model.

[0095] Significantly improve optimization speed and efficiency through dimensionality reduction and intelligent optimization algorithms. Ensure optimal design parameters through dynamic optimization. Reduce computational complexity and conserve computing resources through dimensionality reduction. Improve design reliability and stability through multiple rounds of iterative optimization.

[0096] See also Figure 2 As shown, Figure 2 1 is a schematic diagram of the structure of a hyperbolic curtain wall parametric modeling dynamic optimization device 200 provided in an embodiment of the present application. This hyperbolic curtain wall parametric modeling dynamic optimization device 200 is used to execute the steps of the hyperbolic curtain wall parametric modeling dynamic optimization method described in each of the above embodiments. This hyperbolic curtain wall parametric modeling dynamic optimization device 200 can be a single server or a server cluster, or it can be a terminal, such as a handheld terminal, a laptop computer, a wearable device, or a robot.

[0097] like Figure 2 As shown, the hyperbolic curtain wall parameter modeling dynamic optimization device 200 includes:

[0098] The target acquisition module 201 is used to obtain the construction plan of the hyperbolic curtain wall to be optimized, the environmental information of the hyperbolic curtain wall setting, and the surface design target corresponding to the hyperbolic curtain wall model;

[0099] The outline construction module 202 is used to construct a preliminary outline corresponding to the hyperbolic curtain wall according to the environmental information, the curved surface design target and the construction plan;

[0100] A plane parsing module 203 is used to parse the construction plan to obtain multiple component types and component parameters and component positions corresponding to each component type;

[0101] An environment construction module 204 is used to construct a finite element simulation model based on the environment information, the construction plan, component parameters and component positions, and optimize the objective function of the target component according to the curved surface design;

[0102] The avoidance completion module 205 is used to dynamically optimize the component parameters and component positions corresponding to each component type in the finite element simulation model according to the optimization objective function and the preliminary shape contour, output the optimized component parameters and component positions corresponding to each component type, and complete the avoidance design of multiple components in the hyperbolic curtain wall.

[0103] In some embodiments, constructing a preliminary outer contour corresponding to the hyperbolic curtain wall based on the environmental information, the curved surface design target, and the construction plan includes: performing image recognition on the construction plan and converting it into a preset document format; obtaining constraint parameters corresponding to the hyperbolic curtain wall based on the curved surface design target, the constraint parameters including at least a minimum bending radius and a maximum allowable deviation; calculating preliminary contour parameters corresponding to the hyperbolic curtain wall based on the constraint parameters, the construction plan in a preset document format, and the environmental information; and constructing the preliminary outer contour corresponding to the hyperbolic curtain wall based on the preliminary contour parameters.

[0104] Exemplarily, the calculating of preliminary contour parameters corresponding to the hyperbolic curtain wall according to the constraint parameters, the construction plan in a preset document format, and the environmental information includes: obtaining a construction plan gradient tensor corresponding to the construction plan; constructing an environmental factor matrix and an environmental sensitivity coefficient according to the environmental information; the environmental factor matrix includes at least a wind load coefficient, a temperature gradient, a snow load density, and a seismic coefficient; calculating a constraint balance factor according to the maximum allowable deviation and the minimum bending radius based on a softmax function; and calculating a contour parameter matrix corresponding to the preliminary outer contour according to the constraint balance factor, the construction plan gradient tensor, the environmental factor matrix, the environmental sensitivity coefficient, the maximum allowable deviation, and the minimum bending radius.

[0105] It should be noted that, in some embodiments, the expression of the profile parameter matrix includes:

[0106] ;

[0107] in, is the profile parameter matrix, is the minimum bending radius, is the maximum allowable deviation, is the gradient tensor of the construction plane, is the construction plan coordinate matrix, is the environmental factor matrix, is the environmental sensitivity coefficient, is the constraint balance factor, is a dynamic activation function.

[0108] In some embodiments, optimizing the objective function according to the curved surface design target component includes: constructing a geometric conformality constraint corresponding to the hyperbolic curtain wall according to the curved surface design target; and constructing the optimization objective function according to the geometric conformality constraint; wherein the expression of the geometric conformality constraint includes:

[0109] ;

[0110] in, is the geometric conformality constraint, is the surface parameterization matrix of the construction plan, is the discretization matrix of the target surface corresponding to the hyperbolic curtain wall, is the adaptive weight, is the target Gaussian curvature distribution, is the curvature sensitive weight, is the surface gradient operator, which is used to calculate the first-order geometric change rate of the surface. is the Frobenius norm, which measures the overall deviation of the gradient field, is the Gaussian curvature, represents the surface corresponding to the hyperbolic curtain wall, express The area of the infinitesimal element on .

[0111] Exemplarily, before optimizing the objective function according to the curved surface design target component, the method further includes: constructing structural performance constraints, manufacturing constraints, and avoidance constraints corresponding to the hyperbolic curtain wall according to the curved surface design target; constructing environmental constraints according to the environmental information, so as to construct the optimization objective function according to the geometric conformality constraints, structural performance constraints, manufacturing constraints, avoidance constraints, and environmental constraints.

[0112] In some embodiments, the dynamic optimization of component parameters and component positions corresponding to each component type in the finite element simulation model according to the optimization objective function and the preliminary shape contour includes: performing orthogonal decomposition and dimensionality reduction on the component parameters and component positions; setting an iterative format corresponding to the optimization of the component parameters and component positions; determining a convergence condition according to the surface design objective; completing the configuration of the dynamic optimization solver according to the iterative format and convergence condition; and dynamically optimizing the component parameters and component positions corresponding to each component type in the finite element simulation model under the configured solver according to the optimization objective function and the preliminary shape contour.

[0113] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the hyperbolic curtain wall parametric modeling dynamic optimization device and each module described above can refer to the corresponding processes in the embodiments of the hyperbolic curtain wall parametric modeling dynamic optimization method described in the above embodiments, and will not be repeated here.

[0114] The above-mentioned dynamic optimization method for parametric modeling of hyperbolic curtain wall can be realized in the form of a computer program. The computer program can be used in Figure 2 Run on the device shown.

[0115] See also Figure 3 , Figure 3 1 is a schematic block diagram of the structure of a computer device provided in an embodiment of the present application. The computer device includes a processor, a memory, and a network interface connected via a device bus, wherein the memory may include a storage medium and an internal memory.

[0116] The storage medium can store an operating device and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any one of the hyperbolic curtain wall parametric modeling dynamic optimization methods.

[0117] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0118] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any one of the hyperbolic curtain wall parametric modeling dynamic optimization methods.

[0119] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the terminal to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0120] It should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0121] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0122] Obtaining a construction plan of the hyperbolic curtain wall to be optimized, environmental information of the hyperbolic curtain wall setting, and a surface design target corresponding to the hyperbolic curtain wall model;

[0123] Constructing a preliminary outline corresponding to the hyperbolic curtain wall according to the environmental information, the curved surface design target and the construction plan;

[0124] Parsing the construction plan to obtain multiple component types and component parameters and component positions corresponding to each component type;

[0125] Constructing a finite element simulation model based on the environmental information, construction plan, component parameters and component positions, and optimizing an objective function based on the surface design target component;

[0126] According to the optimization objective function and the preliminary shape contour, the component parameters and component positions corresponding to each component type in the finite element simulation model are dynamically optimized, and the optimized component parameters and component positions corresponding to each component type are output to complete the avoidance design of multiple components in the hyperbolic curtain wall.

[0127] In some embodiments, constructing a preliminary outer contour corresponding to the hyperbolic curtain wall based on the environmental information, the curved surface design target, and the construction plan includes: performing image recognition on the construction plan and converting it into a preset document format; obtaining constraint parameters corresponding to the hyperbolic curtain wall based on the curved surface design target, the constraint parameters including at least a minimum bending radius and a maximum allowable deviation; calculating preliminary contour parameters corresponding to the hyperbolic curtain wall based on the constraint parameters, the construction plan in a preset document format, and the environmental information; and constructing the preliminary outer contour corresponding to the hyperbolic curtain wall based on the preliminary contour parameters.

[0128] Exemplarily, the calculating of preliminary contour parameters corresponding to the hyperbolic curtain wall according to the constraint parameters, the construction plan in a preset document format, and the environmental information includes: obtaining a construction plan gradient tensor corresponding to the construction plan; constructing an environmental factor matrix and an environmental sensitivity coefficient according to the environmental information; the environmental factor matrix includes at least a wind load coefficient, a temperature gradient, a snow load density, and a seismic coefficient; calculating a constraint balance factor according to the maximum allowable deviation and the minimum bending radius based on a softmax function; and calculating a contour parameter matrix corresponding to the preliminary outer contour according to the constraint balance factor, the construction plan gradient tensor, the environmental factor matrix, the environmental sensitivity coefficient, the maximum allowable deviation, and the minimum bending radius.

[0129] It should be noted that, in some embodiments, the expression of the profile parameter matrix includes:

[0130] ;

[0131] in, is the profile parameter matrix, is the minimum bending radius, is the maximum allowable deviation, is the gradient tensor of the construction plane, is the construction plan coordinate matrix, is the environmental factor matrix, is the environmental sensitivity coefficient, is the constraint balance factor, is a dynamic activation function.

[0132] In some embodiments, optimizing the objective function according to the curved surface design target component includes: constructing a geometric conformality constraint corresponding to the hyperbolic curtain wall according to the curved surface design target; and constructing the optimization objective function according to the geometric conformality constraint; wherein the expression of the geometric conformality constraint includes:

[0133] ;

[0134] in, is the geometric conformality constraint, is the surface parameterization matrix of the construction plan, is the discretization matrix of the target surface corresponding to the hyperbolic curtain wall, is the adaptive weight, is the target Gaussian curvature distribution, is the curvature sensitive weight, is the surface gradient operator, which is used to calculate the first-order geometric change rate of the surface. is the Frobenius norm, which measures the overall deviation of the gradient field, is the Gaussian curvature, represents the surface corresponding to the hyperbolic curtain wall, express The area of the infinitesimal element on .

[0135] Exemplarily, before optimizing the objective function according to the curved surface design target component, the method further includes: constructing structural performance constraints, manufacturing constraints, and avoidance constraints corresponding to the hyperbolic curtain wall according to the curved surface design target; constructing environmental constraints according to the environmental information, so as to construct the optimization objective function according to the geometric conformality constraints, structural performance constraints, manufacturing constraints, avoidance constraints, and environmental constraints.

[0136] In some embodiments, the dynamic optimization of component parameters and component positions corresponding to each component type in the finite element simulation model according to the optimization objective function and the preliminary shape contour includes: performing orthogonal decomposition and dimensionality reduction on the component parameters and component positions; setting an iterative format corresponding to the optimization of the component parameters and component positions; determining a convergence condition according to the surface design objective; completing the configuration of the dynamic optimization solver according to the iterative format and convergence condition; and dynamically optimizing the component parameters and component positions corresponding to each component type in the finite element simulation model under the configured solver according to the optimization objective function and the preliminary shape contour.

[0137] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the computer equipment and each module described above can refer to the corresponding processes in the method embodiments described in the above embodiments, and will not be repeated here.

[0138] The present application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor implements the steps of the dynamic optimization method for parametric modeling of hyperbolic curtain walls as provided in any embodiment of the present application.

[0139] The computer-readable storage medium may be an internal storage unit of the computer device described in the aforementioned embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a flash memory card, etc., equipped on the computer device.

[0140] It should be noted that technical personnel in the relevant field can clearly understand that for the convenience and conciseness of description, the specific working processes of the storage medium and each module described above can refer to the corresponding processes in the method embodiments described in the above embodiments, and will not be repeated here.

[0141] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A dynamic optimization method for parametric modeling of hyperbolic curtain walls, characterized in that: include: Obtaining a construction plan of the hyperbolic curtain wall to be optimized, environmental information of the hyperbolic curtain wall setting, and a surface design target corresponding to the hyperbolic curtain wall model; Constructing a preliminary outline corresponding to the hyperbolic curtain wall according to the environmental information, the curved surface design target and the construction plan; Parsing the construction plan to obtain multiple component types and component parameters and component positions corresponding to each component type; A finite element simulation model is constructed based on the environmental information, the construction plan, the component parameters, and the component positions, and an objective function is optimized based on the surface design target component, including: constructing a geometric conformality constraint corresponding to the hyperbolic curtain wall based on the surface design target; constructing the optimization objective function based on the geometric conformality constraint; wherein the expression of the geometric conformality constraint includes: ； in, is the geometric conformality constraint, is the surface parameterization matrix of the construction plan, is the discretization matrix of the target surface corresponding to the hyperbolic curtain wall, is the adaptive weight, is the target Gaussian curvature distribution, is the curvature sensitive weight, is the surface gradient operator, which is used to calculate the first-order geometric change rate of the surface. is the Frobenius norm, which measures the overall deviation of the gradient field, is the Gaussian curvature, represents the surface corresponding to the hyperbolic curtain wall, express The area of the infinitesimal element on is the construction plan coordinate matrix; According to the optimization objective function and the preliminary shape contour, the component parameters and component positions corresponding to each component type in the finite element simulation model are dynamically optimized, and the optimized component parameters and component positions corresponding to each component type are output to complete the avoidance design of multiple components in the hyperbolic curtain wall.

2. The method according to claim 1, characterized in that The step of constructing a preliminary outer contour corresponding to the hyperbolic curtain wall according to the environmental information, the curved surface design target, and the construction plan includes: Performing image recognition on the construction plan and converting it into a preset document format; Obtaining constraint parameters corresponding to the hyperbolic curtain wall according to the curved surface design target, wherein the constraint parameters include at least a minimum bending radius and a maximum allowable deviation; Calculating preliminary contour parameters corresponding to the hyperbolic curtain wall according to the constraint parameters, the construction plan in a preset document format, and environmental information; A preliminary outer contour corresponding to the hyperbolic curtain wall is constructed according to the preliminary contour parameters.

3. The method according to claim 2, characterized in that The calculating of preliminary contour parameters corresponding to the hyperbolic curtain wall according to the constraint parameters, the construction plan in a preset document format, and environmental information includes: Obtaining a construction plan gradient tensor corresponding to the construction plan; Constructing an environmental factor matrix and an environmental sensitivity coefficient based on the environmental information; the environmental factor matrix includes at least a wind load coefficient, a temperature gradient, a snow load density, and a seismic coefficient; Calculating a constraint balance factor based on the maximum allowable deviation and the minimum bending radius based on a softmax function; The contour parameter matrix corresponding to the preliminary outer contour is calculated according to the constraint balance factor, the construction plan gradient tensor, the environmental factor matrix, the environmental sensitivity coefficient, the maximum allowable deviation and the minimum bending radius.

4. The method according to claim 3, characterized in that The expression of the profile parameter matrix includes: ； in, is the profile parameter matrix, is the minimum bending radius, is the maximum allowable deviation, is the gradient tensor of the construction plane, is the construction plan coordinate matrix, is the environmental factor matrix, is the environmental sensitivity coefficient, is the constraint balance factor, is a dynamic activation function.

5. The method according to claim 1, wherein Before optimizing the objective function according to the curved surface design target component, the method further includes: Constructing structural performance constraints, manufacturing constraints, and avoidance constraints corresponding to the hyperbolic curtain wall according to the curved surface design objectives; Environmental constraints are constructed according to the environmental information, so as to construct the optimization objective function according to the geometric conformality constraints, structural performance constraints, manufacturing constraints, avoidance constraints and environmental constraints.

6. The method according to claim 1, wherein The dynamically optimizing the component parameters and component positions corresponding to each component type in the finite element simulation model according to the optimization objective function and the preliminary shape profile includes: Performing orthogonal decomposition and dimensionality reduction on the component parameters and component positions; Setting an iterative format corresponding to the component parameter and component position optimization; Determining a convergence condition according to the surface design goal; completing a solver configuration for the dynamic optimization according to the iteration format and convergence conditions; According to the optimization objective function and the preliminary shape profile, component parameters and component positions corresponding to each component type in the finite element simulation model are dynamically optimized under the configured solver.

7. A hyperbolic curtain wall parametric modeling dynamic optimization device, characterized in that: include: A target acquisition module is used to obtain the construction plan of the hyperbolic curtain wall to be optimized, the environmental information of the hyperbolic curtain wall setting, and the surface design target corresponding to the hyperbolic curtain wall model; A contour construction module, configured to construct a preliminary outer contour corresponding to the hyperbolic curtain wall according to the environmental information, the curved surface design target and the construction plan; A plane parsing module, configured to parse the construction plan to obtain a plurality of component types and component parameters and component positions corresponding to each component type; An environment construction module is used to construct a finite element simulation model based on the environment information, construction plan, component parameters and component positions, and optimize the objective function based on the surface design target component, including: constructing a geometric conformality constraint corresponding to the hyperbolic curtain wall based on the surface design target; constructing the optimization objective function based on the geometric conformality constraint; wherein the expression of the geometric conformality constraint includes: ； in, is the geometric conformality constraint, is the surface parameterization matrix of the construction plan, is the discretization matrix of the target surface corresponding to the hyperbolic curtain wall, is the adaptive weight, is the target Gaussian curvature distribution, is the curvature sensitive weight, is the surface gradient operator, which is used to calculate the first-order geometric change rate of the surface. is the Frobenius norm, which measures the overall deviation of the gradient field, is the Gaussian curvature, represents the surface corresponding to the hyperbolic curtain wall, express The area of the infinitesimal element on is the construction plan coordinate matrix; The avoidance completion module is used to dynamically optimize the component parameters and component positions corresponding to each component type in the finite element simulation model according to the optimization objective function and the preliminary shape contour, output the optimized component parameters and component positions corresponding to each component type, and complete the avoidance design of multiple components in the hyperbolic curtain wall.

8. A computer device, characterized in that: The method comprises a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and implement the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program. When the computer-readable instructions are executed by a processor, one or more processors are caused to perform the steps of the method according to any one of claims 1 to 6.

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