Hyperbolic curtain wall parametric modeling dynamic optimization method, device, equipment and medium

Abstract

The invention provides a hyperbolic curtain wall parametric modeling dynamic optimization method and device, equipment and a medium. The method comprises the steps that a construction plan of a hyperbolic curtain wall to be optimized, environment information set by the hyperbolic curtain wall and a curved surface design target corresponding to a hyperbolic curtain wall model are obtained; according to the environment information, the curved surface design target and the construction plane graph, a preliminary outline corresponding to the hyperbolic curtain wall is constructed; the construction plan is analyzed, and a plurality of component types and component parameters and component positions corresponding to the component types are obtained; constructing a finite element simulation model according to the environment information, the construction plane graph, the component parameters and the component positions, and optimizing a target function according to a curved surface design target component; and according to the optimization objective function and the initial contour, dynamically optimizing the component parameters and component positions corresponding to each component type in the finite element simulation model, outputting the optimized component parameters and component positions corresponding to each component type, and completing the avoidance design of the 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 characteristics. However, the design and construction of hyperbolic curtain walls face many challenges, especially the problem of avoidance design in complex environments. Traditional design methods usually rely on experienced engineers to manually adjust parameters, which is not only time-consuming and labor-intensive, but also difficult to ensure the optimality of the final design solution. Especially when multiple factors need to be considered, how to achieve an aesthetically pleasing and cost-effective solution while meeting functional requirements has become an urgent problem to be solved. Summary of the invention

[0003] This application provides a method, device, equipment and medium for dynamic optimization of parametric modeling of hyperbolic curtain walls, aiming to solve the problem that traditional design methods usually rely on experienced engineers to manually adjust parameters, which is not only time-consuming and labor-intensive, but also difficult to ensure the optimality of the final design solution. Especially when multiple factors need to be considered, how to achieve an aesthetically pleasing and cost-effective solution while meeting functional requirements has become an urgent problem to be solved.

[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 a 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 shape 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 according to the environmental information, the construction plan, component parameters and component positions, and optimizing an objective function according to the surface design target component;

[0009] The component parameters and component positions corresponding to each component type in the finite element simulation model are dynamically optimized according to the optimization objective function and the preliminary shape contour, 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 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; acquiring constraint parameters corresponding to the hyperbolic curtain wall according to 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 according to the constraint parameters, the construction plan in a preset document format and the environmental information; and constructing a preliminary outer contour corresponding to the hyperbolic curtain wall according to the preliminary contour parameters.

[0011] Exemplarily, the method of calculating the 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, the optimizing 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; 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 representation 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 on the infinitesimal element.

[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 the 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 acquire 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, used 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, used to parse the construction plane drawing, obtain multiple component types and component parameters and component positions corresponding to each component type;

[0024] An environment construction module, used to construct a finite element simulation model according to the environment information, construction plan, component parameters and component positions, and to 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 a 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 a method as provided in any embodiment of the present application.

[0028] The present application provides a method, device, equipment and medium for dynamic optimization of parametric modeling of hyperbolic curtain wall, by collecting detailed construction plan drawings, including the overall layout, size, structural details, etc. of the building. Collect environmental information of the project location, such as climate conditions (temperature, humidity, wind speed, etc.), lighting conditions, geographical location, etc. Clarify the design goals of the hyperbolic curtain wall, including specific requirements in terms of aesthetics, functionality, economy, etc. Use parametric design software (such as Rhino, Grasshopper, etc.) to generate a preliminary hyperbolic curtain wall outline according to the construction plan drawing and environmental information. This stage focuses on the design at the macro level to ensure that the basic framework can meet the functional requirements and lay the foundation for subsequent refinement and adjustment. Perform a preliminary evaluation of the generated preliminary model to ensure that it conforms to the design intent in terms of geometry and can be physically realized. Analyze the various types of components that constitute the hyperbolic curtain wall from the construction plan drawing, such as glass panels, steel skeletons, connectors, etc. Extract the specific parameters of each component, including size, material, thickness, etc. Record the relative position relationship of each component in the structure 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, Abaqus, etc.). This model not only takes into account the constraints on physical properties, but also incorporates factors such as aesthetic considerations. According to the surface design goals, the optimization objective function is defined. The optimization objectives can be multifaceted, such as minimizing material costs, maximizing structural stability, optimizing lighting effects, etc. The objective function is solved by an optimization algorithm (such as a genetic algorithm, a particle swarm optimization algorithm, etc.), and the specific parameter values ​​of each component and its spatial configuration are automatically adjusted. This process is dynamic, and the algorithm will iteratively try new combinations until the best design solution that best meets all preset conditions is found. In each iteration, check whether the optimization result has converged to the global optimal solution. If the convergence conditions are met, stop the iteration; otherwise, continue to optimize. Finally, the system will output the exact parameter values ​​and precise placement positions of each optimized component, thereby completing the entire avoidance design process. Generate a detailed optimization report, including the comparison before and after optimization, the evaluation results of various indicators, etc., for reference by designers and engineers.

[0029] Suppose there is a large public building project located in a coastal city. Its exterior wall is planned to use a streamlined hyperbolic glass curtain wall to enhance the visual effect and improve the efficiency of natural lighting. When using this method, you can follow the following steps: Collect meteorological data of the project location, such as annual average temperature, humidity, wind speed, etc. Obtain a sunshine time distribution map to understand the lighting conditions in different seasons and time periods. Obtain detailed construction plans and design intent instructions from the architect. Use Rhino and Grasshopper to draw a 3D conceptual model that meets the architect's creative intent. Perform a preliminary evaluation of the preliminary model to ensure that it meets the design intent in terms of geometry and can be physically realized. Extract all the types of materials involved (such as steel skeletons, laminated glass panels, etc.) and their expected installation coordinates from the detailed construction blueprint. Record the specific parameters of each component, such as length, width, thickness, etc. Establish a composite FEM model in ANSYS that includes multiple indicators such as static stability analysis and thermal performance evaluation. Define the optimization objective function based on the design goals, such as minimizing material costs, maximizing structural stability, optimizing lighting effects, etc. Run the optimization program to let the computer automatically explore the best structural form and material selection scheme. Through genetic algorithm or particle swarm optimization algorithm, the parameter values ​​and positions of each component are adjusted iteratively until the optimal solution is found. After completion, the designer can directly formulate detailed construction guidance documents based on the recommendation report provided by the software. Generate a detailed optimization report, including the comparison before and after optimization, the evaluation results of various indicators, etc.

[0030] Compared with the traditional manual adjustment method, this method can significantly shorten the design cycle and reduce labor costs. Through automated tools, designers can complete complex calculations and adjustments faster, thereby improving overall work efficiency. Supported by scientific and rigorous mathematical models, the final results are more reliable and stable, reducing the chance of rework caused by human errors. The optimization algorithm can find the global optimal solution to ensure that the design scheme can achieve the best state in all aspects. Encouraging the exploration of more novel and unique styles will help promote the development and progress of the field of architectural design. Parametric design and optimization methods make it easier for designers to try different design schemes, thereby inspiring more innovative inspiration. Rational use of resources and reduction of unnecessary waste are conducive to promoting the implementation of the concept of green and sustainable urban construction. By optimizing material use and structural design, the overall cost of the project can be significantly reduced while reducing the impact on the environment. This method not only takes into account the safety and stability of the structure, but also takes into account the aesthetics and economy, and realizes the comprehensive optimization of multiple factors. This enables the final design scheme to better meet the needs of owners and users.

[0031] In summary, the proposed hyperbolic curtain wall parametric modeling dynamic optimization method 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 drawings required for use in the description of the embodiments will be briefly introduced below. 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 paying any creative work.

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

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

[0036] Figure 3 It 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 the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0039] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the 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 change according to actual conditions.

[0040] It should be understood that, in order to facilitate the clear description of the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, the words "first", "second", etc. are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art can understand that the words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not necessarily limit the difference.

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

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

[0043] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can 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 characteristics. However, the design and construction of hyperbolic curtain walls face many challenges, especially the problem of avoidance design in complex environments. Traditional design methods usually rely on experienced engineers to manually adjust parameters, which is not only time-consuming and labor-intensive, but also difficult to ensure the optimality of the final design solution. Especially when multiple factors need to be considered, how to achieve an aesthetically pleasing and cost-effective solution while meeting functional requirements has become an urgent problem to be solved.

[0045] To solve the above problems, 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 surface design target corresponding to the hyperbolic curtain wall model.

[0047] Specifically, by collecting all relevant information about the photovoltaic modules to be designed or optimized, including but not limited to the specific conditions of the installation environment (such as light intensity, temperature changes, etc.), and the user's requirements for the appearance and function of the modules. For example, data is collected through on-site inspections, customer interviews, etc.; professional software tools are used to simulate the performance of photovoltaic modules under different environmental conditions. If the goal is to set up photovoltaic modules that can serve as partition walls and power generation sources in a semi-open office space, it is necessary to understand the sunlight exposure pattern of the space, the temperature difference between indoors and outdoors, and other factors in detail. This ensures that the design plan is more in line with the needs of the actual application scenario and improves the practicality of the final product.

[0048] The construction plan is usually completed by the architectural design team during the project design phase. It can be extracted from the Building Information Model (BIM) system, which integrates various aspects of the building, including the floor plan and dimensioning of the curtain wall. For example, for a hyperbolic curtain wall project of a large commercial complex, the design team used Revit software to create a detailed BIM model. By exporting files in a specific format (such as DWG or DXF), the construction plan of the hyperbolic curtain wall can be obtained. The plan will clearly mark the boundaries of the curtain wall, the location of doors and windows, and the connection points with other building structures. Environmental information includes geographical environment, meteorological conditions, etc. Geographical environment information can be obtained through the Geographic Information System (GIS), such as the topography of the project site and the distribution of surrounding buildings. Meteorological condition information can be obtained from the local meteorological department, including wind speed, wind direction, sunshine time, temperature range, etc. Take a hyperbolic curtain wall building in a coastal city as an example. GIS data shows that there are other high-rise buildings around the building, which will affect the ventilation and lighting of the curtain wall. Data obtained from the meteorological department show that the dominant wind direction in the area is southeast wind all year round, and there are many heavy rains in summer. This information is crucial for the subsequent curtain wall design. The surface design goals are usually determined by the architect based on the overall style and functional requirements of the building. For example, the designer hopes that the hyperbolic curtain wall will present a smooth curve shape to match the modern sense of the building; or require the curtain wall to produce unique light and shadow effects from different perspectives. These design goals 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 collected in the previous step, start drafting the basic shape and layout of the photovoltaic modules. Use CAD or other 3D modeling software for preliminary design. This application does not restrict the type of 3D software. Design a modular photovoltaic panel that can be freely combined into different sizes and shapes, which can be used as a wall decoration and can generate electricity efficiently. Lay the foundation for subsequent precise adjustments and help to quickly iterate the design plan.

[0051] According to 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 wind, 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, considering 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 objectives. 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 preliminary 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 functions in your CAD software to accurately place the surface model on the plan view.

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

[0053] Specifically, we conduct an in-depth analysis of the existing design drawings to clarify the key dimensions and other important properties of each component. We use BIM (Building Information Modeling) and other technical means to digitally process the design files. We determine the optimal length-width ratio, thickness and other physical properties of each photovoltaic panel. This facilitates subsequent calculations and analysis to ensure coordination between the various parts.

[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, connectors, etc. By analyzing the colors, line styles, and sizes of different graphics in the plan, various component types can be accurately identified. For each component type, its corresponding parameters are extracted from the construction plan. For example, for glass panels, its size, thickness, color and other parameters need to be obtained; for aluminum alloy frames, its cross-sectional shape, size, material and other parameters need to be obtained. These parameters can be obtained by measuring the size of the graphics in the plan and consulting relevant design description documents. Determine the position of each component according to the coordinate system in the construction plan. The position of the component on the plane can be determined by reading the coordinates of the center point or corner point of the component in the plan. At the same time, combined with the preliminary outline of the hyperbolic curtain wall, the position of the component in three-dimensional space is determined.

[0055] Step S104: construct a finite element simulation model according to 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 containing all relevant factors is created, and the objective function for performance optimization is set. Finite element analysis (FEA) software is used to conduct virtual testing. The goal is to maximize the total power generation of the entire system within a specific time period while minimizing material costs. Potential problems can be discovered and improvements can be made before actual manufacturing, saving time and resources.

[0057] Use finite element analysis software (such as ANSYS or ABAQUS) to build a finite element simulation model of the hyperbolic curtain wall based on environmental information, construction plan, component parameters and component location. First, import the preliminary outline and component information of the hyperbolic curtain wall into the finite element software to build a geometric model. Then, according to the material properties and connection methods of the components, define the unit type and material properties, and mesh the model. Finally, according to the environmental information, apply the corresponding boundary conditions and loads, such as wind speed, temperature change, etc. According to the surface design goals, construct an optimization objective function. The optimization objective function is usually a multi-objective function that needs to consider multiple factors, such as the aesthetics of the curtain wall, structural safety, and economy. For example, the objective function can be defined as the weighted sum of minimizing the wind load response of the curtain wall, maximizing the daylighting area of ​​the curtain wall, and minimizing the construction cost of the curtain wall. The specific weights can be adjusted according to the actual needs of the project.

[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 variable values ​​in the model are continuously adjusted according to the set objective function until the optimal solution is found. The optimal configuration is automatically found using intelligent optimization algorithms such as genetic algorithms and particle swarm optimization. By repeatedly testing different arrangements and combinations of photovoltaic panels, a solution that meets both aesthetic requirements and achieves the highest efficiency is found. The final product is not only beautiful in appearance but also has excellent performance, meeting the diverse needs of users.

[0060] Select appropriate dynamic optimization algorithms, such as genetic algorithms, particle swarm algorithms, etc., to optimize the component parameters and component positions in the finite element simulation model. These algorithms have global search capabilities and can find the optimal solution in a large parameter space. The optimization objective function and the finite element simulation model are used as input, and the selected optimization algorithm is used for iterative calculation. In each iteration, the algorithm calculates the value of the objective function based on the current component parameters and component positions, and adjusts the parameters and positions according to certain rules to gradually approach the optimal solution. At the same time, the finite element simulation model is used to analyze each adjusted solution and evaluate its performance. When the optimization algorithm meets the convergence conditions (such as the value of the objective function no longer changes or the change is less than a certain threshold), the component parameters and component positions corresponding to each component type after optimization are output. These parameters and position information can be used to guide the construction and installation of hyperbolic curtain walls, realize the avoidance design of multiple components, and ensure that the curtain wall meets the functional requirements while achieving an aesthetic and cost-effective solution.

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

[0062] A method for dynamic optimization of parametric modeling of a hyperbolic curtain wall provided in an embodiment of the present application is provided by collecting detailed construction plans, including the overall layout, size, structural details, etc. of the building. Environmental information of the project location, such as climate conditions (temperature, humidity, wind speed, etc.), lighting conditions, geographical location, etc., is collected. The design objectives of the hyperbolic curtain wall are clarified, including specific requirements in terms of aesthetics, functionality, economy, etc. A preliminary hyperbolic curtain wall profile is generated based on the construction plan and environmental information using parametric design software (such as Rhino, Grasshopper, etc.). This stage focuses on the design at the macro level to ensure that the basic framework can meet the functional requirements and lay the foundation for subsequent refinement and adjustment. The generated preliminary model is preliminarily evaluated to ensure that it conforms to the design intent in terms of geometry and can be physically realized. Various types of components that constitute the hyperbolic curtain wall, such as glass panels, steel skeletons, connectors, etc., are parsed from the construction plan. Specific parameters of each component are extracted, including size, material, thickness, etc. The relative position relationship of each component in the structure is 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, Abaqus, etc.). This model not only takes into account the constraints on physical properties, but also incorporates factors such as aesthetic considerations. According to the surface design goals, the optimization objective function is defined. The optimization objectives can be multifaceted, such as minimizing material costs, maximizing structural stability, optimizing lighting effects, etc. The objective function is solved by an optimization algorithm (such as a genetic algorithm, a particle swarm optimization algorithm, etc.), and the specific parameter values ​​of each component and its spatial configuration are automatically adjusted. This process is dynamic, and the algorithm will iteratively try new combinations until the best design solution that best meets all preset conditions is found. In each iteration, check whether the optimization result has converged to the global optimal solution. If the convergence conditions are met, stop the iteration; otherwise, continue to optimize. Finally, the system will output the exact parameter values ​​and precise placement positions of each optimized component, thereby completing the entire avoidance design process. Generate a detailed optimization report, including the comparison before and after optimization, the evaluation results of various indicators, etc., for reference by designers and engineers.

[0063] Suppose there is a large public building project located in a coastal city. Its exterior wall is planned to use a streamlined hyperbolic glass curtain wall to enhance the visual effect and improve the efficiency of natural lighting. When using this method, you can follow the following steps: Collect meteorological data of the project location, such as annual average temperature, humidity, wind speed, etc. Obtain a sunshine time distribution map to understand the lighting conditions in different seasons and time periods. Obtain detailed construction plans and design intent instructions from the architect. Use Rhino and Grasshopper to draw a 3D conceptual model that meets the architect's creative intent. Perform a preliminary evaluation of the preliminary model to ensure that it meets the design intent in terms of geometry and can be physically realized. Extract all the types of materials involved (such as steel skeletons, laminated glass panels, etc.) and their expected installation coordinates from the detailed construction blueprint. Record the specific parameters of each component, such as length, width, thickness, etc. Establish a composite FEM model in ANSYS that includes multiple indicators such as static stability analysis and thermal performance evaluation. Define the optimization objective function based on the design goals, such as minimizing material costs, maximizing structural stability, optimizing lighting effects, etc. Run the optimization program to let the computer automatically explore the best structural form and material selection scheme. Through genetic algorithm or particle swarm optimization algorithm, the parameter values ​​and positions of each component are adjusted iteratively until the optimal solution is found. After completion, the designer can directly formulate detailed construction guidance documents based on the recommendation report provided by the software. Generate a detailed optimization report, including the comparison before and after optimization, the evaluation results of various indicators, etc.

[0064] Compared with the traditional manual adjustment method, this method can significantly shorten the design cycle and reduce labor costs. Through automated tools, designers can complete complex calculations and adjustments faster, thereby improving overall work efficiency. Supported by scientific and rigorous mathematical models, the final results are more reliable and stable, reducing the chance of rework caused by human errors. The optimization algorithm can find the global optimal solution to ensure that the design scheme can achieve the best state in all aspects. Encouraging the exploration of more novel and unique styles will help promote the development and progress of the field of architectural design. Parametric design and optimization methods make it easier for designers to try different design schemes, thereby inspiring more innovative inspiration. Rational use of resources and reduction of unnecessary waste are conducive to promoting the implementation of the concept of green and sustainable urban construction. By optimizing material use and structural design, the overall cost of the project can be significantly reduced while reducing the impact on the environment. This method not only takes into account the safety and stability of the structure, but also takes into account the aesthetics and economy, and realizes the comprehensive optimization of multiple factors. This enables the final design scheme to better meet the needs of owners and users.

[0065] In summary, the proposed hyperbolic curtain wall parametric modeling dynamic optimization method 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 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; acquiring constraint parameters corresponding to the hyperbolic curtain wall according to 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 according to the constraint parameters, the construction plan in a preset document format and the environmental information; and constructing a preliminary outer contour corresponding to the hyperbolic curtain wall according to the preliminary contour parameters.

[0067] The preliminary outline of the hyperbolic curtain wall is constructed according to the environmental information, the surface design target and the construction plan. 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 bending radius and the maximum allowable deviation, according to the surface design target. Calculating the preliminary outline parameters of the hyperbolic curtain wall based on the constraint parameters, the construction plan in the preset document format and the environmental information. Constructing the preliminary outline of the hyperbolic curtain wall according to the 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 to a preset document format (such as DXF or SVG) for subsequent processing. For example, open the construction plan image file. Use the edge detection tool in the image processing software to extract the lines and boundaries in the image. Convert the extracted lines and boundaries to a vector graphics format (such as DXF or SVG) for subsequent calculations and modeling. Save the converted file, ensuring that it is in the correct format and contains all the necessary details. Determine the minimum bending radius and maximum allowable deviation of the hyperbolic curtain wall based on the design specifications and user requirements. For example, the minimum bending radius may be 500mm and the maximum allowable deviation is ±5mm. Determine the materials used and their physical properties, especially the minimum bending radius. Determine the maximum allowable deviation based on project requirements and industry standards. Record these parameters for use in subsequent calculations.

[0069] The gradient tensor of the construction plan is calculated using a numerical analysis method to reflect the changing trend of the plan. The environmental factor matrix includes wind load coefficient, temperature gradient, snow load density, and seismic coefficient. The environmental sensitivity coefficient is used to quantify the degree of influence of these environmental factors on the design. The coordinate data of the construction plan is read from the converted preset document format. The gradient tensor of the construction plan is calculated using a numerical differentiation method. 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 in combination with the maximum allowable deviation and the minimum bending radius. The contour parameter matrix corresponding to the preliminary contour 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. Use the calculated contour parameter matrix to construct the preliminary contour of the hyperbolic curtain wall in the 3D modeling software. For example, use Rhinoceros+Grasshopper for parametric modeling. 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, which indicates the degree of influence of environmental factors on the design. Record the environmental factor matrix and environmental sensitivity coefficient for subsequent calculations. Create a new project in the 3D modeling software. Import the calculated contour parameter matrix. Use the parametric modeling tool to generate a 3D model based on the contour parameter matrix. Adjust the details of the model to ensure that it meets the design requirements. Save the model file for subsequent optimization and verification.

[0071] Exemplarily, the method of calculating the 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] The example details how to calculate preliminary contour parameters based on constraint parameters, a construction plan in a preset document format, and environmental information. The specific steps include: obtaining the construction plan gradient tensor. Constructing the environmental factor matrix and environmental sensitivity coefficient. Calculating the constraint balance factor based on the softmax function. Calculating the contour parameter matrix corresponding to the preliminary shape contour.

[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, including 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 design of the preliminary outline is ensured to be more accurate and reasonable. In combination with environmental factors and constraints, the hyperbolic curtain wall has better stability and durability in practical applications. Potential problems can be discovered and solved in advance, reducing the cost of later modifications and rework. The design can better adapt to different environmental conditions and improve the reliability and efficiency of the overall system. For example, the gradient tensor of the construction plan is calculated using numerical differentiation methods.

[0078] In some embodiments, the optimizing 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; 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 representation 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 on the infinitesimal element.

[0081] The optimization objective function is constructed by coupling multiple constraints to ensure that the curtain wall design meets the geometric conformality, structural performance, manufacturing feasibility and avoidance requirements at the same time. The specific steps include: constructing geometric conformality constraints according to the surface design objectives. Constructing the optimization objective function according to the geometric conformality constraints and other constraints. At the same time, in addition to the geometric conformality constraints, structural performance constraints, manufacturing constraints, avoidance constraints and environmental constraints need to be considered. The specific form and weight of each constraint need to be set according to 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] The geometric conformality constraint can be constructed by determining the target surface and target Gaussian curvature distribution according to the design goal to calculate the geometric conformality constraint. Structural performance constraints consider mechanical requirements such as wind load and snow load. Manufacturing constraints consider processing accuracy and equipment limitations. Avoidance constraints consider spatial constraints such as pipeline crossing. Environmental constraints consider factors such as temperature changes and light.

[0084] By comprehensively considering multiple constraints, a more comprehensive design optimization can be achieved. Ensure that the design is optimal in terms of geometry, structural performance, manufacturing feasibility and environmental adaptability. Through a single optimization process, the time and cost of multiple design iterations can be reduced.

[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 the 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] Through orthogonal decomposition and dimensionality reduction and intelligent optimization algorithms, efficient dynamic optimization of component parameters is achieved. The specific steps include: Orthogonal decomposition and dimensionality reduction: orthogonal decomposition and dimensionality reduction of component parameters and positions. Set the iteration format: set the iteration format for component parameter and position optimization. Determine the convergence condition: determine the convergence condition according to the surface design goal. Configure the solver: complete the solver configuration according to the iteration format and convergence condition. Dynamic optimization: dynamically optimize the component parameters and positions in the finite element simulation model under the configured solver.

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

[0088] Orthogonal decomposition dimensionality reduction: Use PCA to map high-dimensional parameters to low-dimensional space and retain 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, the 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. Determine the convergence condition: the objective function changes less than 1e-5 or reaches the maximum number of iterations. Under the configured solver, dynamically optimize the component parameters and positions in the finite element simulation model.

[0095] Through dimensionality reduction and intelligent optimization algorithms, the optimization speed and efficiency are significantly improved. Through dynamic optimization, the design parameters are ensured to be optimal. Through dimensionality reduction, the computational complexity is reduced and computing resources are saved. Through multiple rounds of iterative optimization, the reliability and stability of the design are improved.

[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. The 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 shown in the above embodiments. The hyperbolic curtain wall parametric modeling dynamic optimization device 200 can be a single server or a server cluster, or the hyperbolic curtain wall parametric modeling dynamic optimization device 200 can be a terminal, which can be a handheld terminal, a laptop computer, a wearable device or a robot, etc.

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

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

[0099] The contour construction module 202 is used 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;

[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 according to the environment information, the construction plan, component parameters and component positions, and to 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 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; acquiring constraint parameters corresponding to the hyperbolic curtain wall according to 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 according to the constraint parameters, the construction plan in a preset document format and the environmental information; and constructing a preliminary outer contour corresponding to the hyperbolic curtain wall according to the preliminary contour parameters.

[0104] Exemplarily, the method of calculating the 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, the optimizing 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; 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 representation 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 on the infinitesimal element.

[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 the 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 simplicity 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 hyperbolic curtain wall parametric modeling dynamic optimization method embodiments described in the above embodiments, and will not be repeated here.

[0114] The above-mentioned hyperbolic curtain wall parametric modeling dynamic optimization method can be implemented 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 dynamic optimization method for parametric modeling of hyperbolic curtain walls.

[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 scheme of the present application, and does not constitute a limitation on the terminal to which the scheme of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

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

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

[0122] Obtaining a construction plan of a 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 shape 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 according to the environmental information, the construction plan, component parameters and component positions, and optimizing an objective function according to the surface design target component;

[0126] The component parameters and component positions corresponding to each component type in the finite element simulation model are dynamically optimized according to the optimization objective function and the preliminary shape contour, 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 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; acquiring constraint parameters corresponding to the hyperbolic curtain wall according to 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 according to the constraint parameters, the construction plan in a preset document format and the environmental information; and constructing a preliminary outer contour corresponding to the hyperbolic curtain wall according to the preliminary contour parameters.

[0128] Exemplarily, the method of calculating the 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, the optimizing 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; 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 representation 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 on the infinitesimal element.

[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 the 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 technical personnel in the relevant field can clearly understand that, for the convenience and conciseness 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, which stores 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 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 foregoing 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 smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash 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 is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for dynamic optimization of parametric modeling of hyperbolic curtain wall, characterized in that: include: Obtaining a construction plan of a 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 shape 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; Constructing a finite element simulation model according to the environmental information, the construction plan, component parameters and component positions, and optimizing an objective function according to the surface design target component; The component parameters and component positions corresponding to each component type in the finite element simulation model are dynamically optimized according to the optimization objective function and the preliminary shape contour, 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 constructing a preliminary shape outline 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; Obtain constraint parameters corresponding to the hyperbolic curtain wall according to the curved surface design target, wherein the constraint parameters at least include a minimum bending radius and a maximum allowable deviation; Calculate 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 the 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 at least includes a wind load coefficient, a temperature gradient, a snow load density and a seismic coefficient; Based on the softmax function, a constraint balance factor is calculated according to the maximum allowable deviation and the minimum bending radius; The contour parameter matrix corresponding to the preliminary shape 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, characterized in that The step of optimizing the objective function by designing the target component according to the curved surface comprises: Constructing a geometric conformality constraint corresponding to the hyperbolic curtain wall according to the surface design target; The optimization objective function is constructed according to 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 representation 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 on the infinitesimal element.

6. The method according to claim 5, characterized in that Before optimizing the objective function according to the curved surface design target component, the method further comprises: According to the curved surface design target, the structural performance constraints, manufacturing constraints and avoidance constraints corresponding to the hyperbolic curtain wall are constructed; 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.

7. The method according to claim 1, characterized in that 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 iteration format corresponding to the optimization of component parameters and component positions; Determining a convergence condition according to the surface design objective; completing the solver configuration for the dynamic optimization according to the iteration format and the convergence condition; 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.

8. A hyperbolic curtain wall parametric modeling dynamic optimization device, characterized in that: include: A target acquisition module is used to acquire 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, used 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, used to parse the construction plane drawing, obtain multiple component types and component parameters and component positions corresponding to each component type; An environment construction module, used to construct a finite element simulation model according to the environment information, construction plan, component parameters and component positions, and to optimize the objective function of the target component according to the surface design; 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.

9. 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 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer-readable instructions are executed by the processor, one or more processors are caused to perform the steps of the method according to any one of claims 1 to 7.

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