Modular energy-saving building design system and method

Abstract

The invention belongs to the technical field of building design, and particularly discloses a modular energy-saving building design system which comprises a parameter constraint module, a model construction module, an energy-saving constraint module, a splitting module, a positioning module and a load analysis module, and based on the system, the invention further discloses a modular energy-saving building design method. The three-dimensional model is optimized through the energy-saving constraint module, the energy-saving requirement of the modular building is met, then the three-dimensional model is divided into the multiple polyhedral space models, the positioning module is adopted to sort all the polyhedral space models and determine the coordinates of the connecting points of the polyhedral space models, and the field assembly work of the modular building is orderly and accurate.

Description

Technical Field

[0001] The invention belongs to the technical field of building design, and in particular relates to a modular energy-saving building design system and method. Background Art

[0002] Modular construction is an innovative construction method. Standardized building modules are mass-produced in factories to ensure the quality and precision of the modules. They are fixed at the construction site using bolt connections, welding, and other methods. The installation process is simple and quick, and it has broad application prospects in residential buildings, commercial buildings, public buildings, and other fields.

[0003] A Chinese patent with publication number CN113392463A discloses a modular building design method based on BIM technology, which applies BIM technology to the entire life cycle of modular building design, production, and on-site construction, and realizes the fine management of the entire life cycle of modular buildings. In the process of using BIM modeling, although the scheme performs collision checks in the model, in the actual assembly process, the positions of the connection points of the building modules need to be determined in advance. Since the connection points of the building modules are the key parts of the building modules and need to withstand multiple forces, deformation within the technical requirements is inevitable, which will affect the positioning of the next building module and make it difficult to ensure the construction accuracy of the entire modular building system. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects in the prior art and provide a modular energy-saving building design system and method.

[0005] A first aspect of the present invention provides a modular energy-saving building design system, comprising:

[0006] Parameter constraint module: used to obtain modular building project planning requirements and set constraints based on the requirements;

[0007] Model building module: build a 3D model of modular buildings based on constraints to form a visual model body;

[0008] An energy-saving constraint module, which selects a passive energy-saving constraint or an active energy-saving constraint to optimize the three-dimensional model based on the modular building project plan; the passive energy-saving constraint is to achieve energy saving through the building design itself, and the active energy-saving constraint is to achieve energy saving through external energy;

[0009] Splitting module: used for dividing the three-dimensional model into a plurality of polyhedral space models based on the functional space, and each of the polyhedral space models is highlighted on the main body of the visualization model;

[0010] Positioning module: used to determine the connection sequence of each polyhedral space model and label each polyhedral space model based on the connection sequence, and obtain the connection point coordinates of each polyhedral space model, and optimize the connection point coordinates of the next polyhedral space model in real time based on the previous polyhedral space model;

[0011] Load analysis module: applying a first load and a second load at the connection points of two adjacent polyhedral space models, obtaining deformation parameters of the connection points, and determining the stability level of the modular building based on the deformation parameters.

[0012] A further solution is that the model building module includes a pre-definition unit, an instruction calling unit and a three-dimensional model building unit;

[0013] The predefined unit defines a plurality of generation instructions based on a general specification for architectural design, each of the generation instructions includes a dialog box for inputting a restriction condition, and each generation instruction generates a standardized building unit model based on the restriction condition;

[0014] The instruction calling unit is used to select and call the standardized building unit model;

[0015] The three-dimensional model building unit is used to build a three-dimensional model of a modular building.

[0016] A further solution is that the model building module also includes a sharing unit, which is communicatively connected to multiple user terminals and is used to share the generation instructions.

[0017] A further solution is that the model building module also includes a permission setting unit, which is used to limit any one of the users to the main control end in a predefined manner when operating on users with different identities at the same time, and users with other identities are defaulted to auxiliary ends. At the same time, the operating authority scope of the main control end and the auxiliary end is determined separately according to the identity limitations.

[0018] A further solution is that the splitting module is a splitting decision model based on a neural network, the calibrated functional splitting rules are input into the neural network tool, and iterative training is performed under set training resources to form the splitting decision model, the three-dimensional model is used as the input of the splitting decision model, and the splitting decision model outputs multiple polyhedral space models after splitting.

[0019] A further solution is that the positioning module optimizes the connection point coordinates of the polyhedral space model in real time through a coordinate optimization model;

[0020] The construction process of the coordinate optimization model is as follows:

[0021] The coordinates of the connection points of two adjacent polyhedral space models after connection are compared with the coordinates before connection and marked by manual experts. The coordinate difference of the connection points of two adjacent polyhedral space models after connection is obtained and coordinate compensation is set. The coordinates of the connection points of the unconnected polyhedral space models are input into the neural network model in sequence according to the time series number for coordinate compensation and the compensated coordinates are output.

[0022] A further solution is that the first load is a wind load, the second load is a seismic load, and the calculation process of the wind load is:

[0023] w k =β z ×μ z ×μ s × o

[0024] Among them, w k is the wind load, β z is the gust coefficient of instantaneous wind pressure, μ z is the wind pressure height variation coefficient, μ s is the wind load shape factor, w o is the basic wind pressure;

[0025] The calculation process of the seismic load is:

[0026] q=ρ E ×α max ×G

[0027] Where q is the seismic load, ρ E is the power amplification factor, α max The maximum value of the horizontal seismic influence coefficient and the G polyhedral space model are the standard values ​​of the gravity load.

[0028] A further solution is that the load analysis module determines the stability level of the modular building through a stability level model;

[0029] The construction process of the stability level model is as follows:

[0030] A large number of wind load-deformation pairs and seismic load-deformation pairs of different levels are obtained and marked by artificial experts; after marking, the wind load-deformation pairs and seismic load-deformation pairs are sequentially input into different neural network units for iterative training; two neural network units are combined to obtain the deformation at the connection point of the polyhedron space model under different wind loads and seismic loads;

[0031] Setting a deformation value threshold and a modular building stability grade corresponding to the deformation value threshold, and obtaining a stability grade model for outputting the modular building stability grade based on the deformation value;

[0032] The wind load-deformation number pairs include different wind loads and deformations at the connection points of the polyhedron space model corresponding to the different wind loads;

[0033] The seismic load-deformation number pairs include different seismic loads and deformations at connection points of the polyhedron space model corresponding to the different seismic loads.

[0034] A second aspect of the present invention provides a modular energy-saving building design method, which uses the above modular energy-saving building design system and includes the following steps:

[0035] Obtain modular building project planning requirements and set constraints based on the requirements;

[0036] Construct a 3D model of the modular building based on the constraints to form the main body of the visual model;

[0037] Selecting a passive energy-saving constraint or an active energy-saving constraint to optimize the three-dimensional model based on the modular building project plan; the passive energy-saving constraint is to achieve energy saving through the building design itself, and the active energy-saving constraint is to achieve energy saving through external energy;

[0038] Dividing the three-dimensional model into a plurality of polyhedral space models based on the functional space, each of the polyhedral space models is highlighted on the visualization model body;

[0039] Determine the connection sequence of each polyhedral space model and label each polyhedral space model based on the connection sequence, obtain the connection point coordinates of each polyhedral space model, and optimize the connection point coordinates of the next polyhedral space model in real time based on the previous polyhedral space model;

[0040] A first load and a second load are applied at the connection points of two adjacent polyhedral space models, deformation parameters of the connection points are obtained, and the stability level of the modular building is determined based on the deformation parameters; the first load is a wind load, and the second load is an earthquake load.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] (1) The present invention constructs a three-dimensional model that meets the project requirements based on the constraints, optimizes the three-dimensional model through the energy-saving constraint module, meets the energy-saving requirements of modular buildings, and then divides the three-dimensional model into multiple polyhedral space models. The positioning module is used to sort each polyhedral space model and determine the coordinates of its connection points, so that the on-site assembly of modular buildings is orderly and accurate. The polyhedral space model is produced and assembled in the factory, and the on-site construction efficiency is high. Compared with traditional buildings, it can significantly shorten the construction period, reduce labor costs, expenses, and management costs, and reduce later maintenance costs. In addition, since the polyhedral space model is produced and assembled in the factory, all materials of the modular building can be recycled or reused, there is no wet operation and no dust during construction, and the production process is green and environmentally friendly, and there is no waste discharge.

[0043] (2) When constructing a model, the present invention also communicates with multiple user terminals through a sharing unit, and can share multiple generation instructions defined based on general architectural design specifications, and limit the authority scope of multiple user terminals to design simultaneously, thereby avoiding design conflicts while sharing resources, improving design efficiency, and reducing over-design.

[0044] (3) During the design phase, the present invention simulates wind loads and seismic loads in the form of external loads to monitor the deformation at the connection points of the polyhedron space model, and outputs the stability level of the modular building through a neural network model, thereby ensuring the strength of the modular building. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The following drawings are only used to illustrate and explain the present invention, and are not used to limit the scope of the present invention, wherein:

[0046] Figure 1 : Schematic diagram of the connection structure of the modular energy-saving building design system of the present invention;

[0047] Figure 2 : Flow chart of modular energy-saving building design method of the present invention;

[0048] In the figure: 1. Parameter constraint module; 2. Energy-saving constraint module; 3. Model building module; 4. Splitting module; 5. Positioning module; 6. Load analysis module; 7. Predefined unit; 8. Instruction calling unit; 9. Three-dimensional model building unit; 10. Sharing unit; 11. Authority setting unit; 12. Splitting decision model; 13. Coordinate optimization model; 14. Stability level model; 15. User end. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution, design method and advantages of the present invention clearer, the present invention is further described in detail by specific embodiments in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0050] Example 1

[0051] This embodiment provides a modular energy-saving building design system, including: a parameter constraint module, a model building module, an energy-saving constraint module, a splitting module, a positioning module and a load analysis module. Specifically, the parameter constraint module is used to obtain the modular building project plan requirements and set constraint conditions based on the requirements, wherein the constraint conditions are thresholds of different dimensions set according to the project plan, such as a functional space quantity threshold, a length threshold, an area threshold, etc.

[0052] The model construction module constructs a three-dimensional model of a modular building based on the constraints to form a visual model body. In this embodiment, the model construction module includes a predefined unit, an instruction call unit and a three-dimensional model construction unit; the predefined unit defines multiple generation instructions based on the general specifications of architectural design, each of which includes a dialog box for inputting constraints, and each generation instruction generates a standardized building unit model based on the constraints; the instruction call unit is used to select and call the standardized building unit model. The three-dimensional model construction unit is used to construct a three-dimensional model of a modular building. In order to improve design efficiency and reduce design costs, a sharing unit is also introduced in the model construction module. The sharing unit can be connected to multiple user terminals in communication. When the user terminal sends a request to the design system, the above-mentioned generation instructions can be shared to perform standardized design. Since the sharing unit can be connected to multiple user terminals at the same time, multiple users can complete collaborative design. In order to ensure the orderly progress of collaborative design, in this embodiment, the main control terminal and the auxiliary terminal can be determined in a predefined manner. Specifically, the above-mentioned model construction module also includes a permission setting unit, which is used to limit the user of any one of the identities to the main control terminal in a predefined manner when operating on users with different identities at the same time, and the users of other identities are defaulted to the auxiliary terminals. At the same time, the operating authority scope of the main control terminal and the auxiliary terminal is determined separately according to the identity limitation.

[0053] The energy-saving constraint module selects passive energy-saving constraints or active energy-saving constraints to optimize the three-dimensional model based on the modular building project plan; the passive energy-saving constraints are to achieve energy saving through the building design itself, and the active energy-saving constraints are to achieve energy saving through external energy sources; specifically, the passive energy-saving constraints include the building layout and size, building spacing and orientation, thermal insulation and heat insulation of the building envelope, natural ventilation and natural lighting, etc., and the active energy-saving constraints can be energy sources such as electricity and natural gas. The modular building can save energy to the greatest extent through the mutual complementation and coordination of passive energy-saving constraints and active energy-saving constraints.

[0054] The splitting module is used to divide the three-dimensional model into several polyhedral space models based on the functional space, and each of the polyhedral space models is highlighted on the main body of the visualization model; in this embodiment, the splitting module is a splitting decision model based on a neural network, and the calibrated functional splitting rules are input into the neural network tool, and iterative training is performed under the set training resources to form the splitting decision model, and the three-dimensional model is used as the input of the splitting decision model, and the splitting decision model outputs multiple split polyhedral space models. Among them, the calibrated functions at least include the building layout, wall structure, door and window structure, office area, rest area, etc. defined by different parameters. Different functions are input into the splitting decision model to obtain different splitting decisions, and different polyhedral space models are obtained based on different splitting decisions. The neural network tool includes an input layer, an output layer, and a hidden layer located between the input layer and the output layer. The neurons in the hidden layer recognize and split the input model and output different polyhedral space models. Specifically, the calibrated functional splitting rules are input into the neural network tool, and iterative training is performed under the set training resources to form the splitting decision model. The three-dimensional model is used as the input of the splitting decision model, and the splitting decision model outputs multiple polyhedral space models after splitting.

[0055] In the above, the positioning module optimizes the connection point coordinates of the polyhedral space model in real time through the coordinate optimization model; the construction process of the coordinate optimization model is: compare the coordinates of the connection points of two adjacent polyhedral space models after connection with the coordinates before connection and perform manual expert marking, obtain the coordinate difference of the connection points of the two adjacent polyhedral space models after connection and set coordinate compensation, input the connection point coordinates of the unconnected polyhedral space model into the neural network model in sequence according to the time series number for coordinate compensation and output the compensated coordinates.

[0056] The positioning module is used to determine the connection sequence of each polyhedral space model and label each polyhedral space model based on the connection sequence, and obtain the connection point coordinates of each polyhedral space model, and optimize the connection point coordinates of the next polyhedral space model in real time based on the previous polyhedral space model; in this embodiment, the positioning module optimizes the connection point coordinates of the polyhedral space model in real time through the coordinate optimization model; the construction process of the coordinate optimization model is: compare the coordinates of the connection points of two adjacent polyhedral space models after connection with the coordinates before connection and perform manual expert marking, obtain the coordinate difference of the connection points of two adjacent polyhedral space models after connection and set coordinate compensation, input the connection point coordinates of the unconnected polyhedral space model into the neural network model in sequence according to the time sequence label for coordinate compensation and output the compensated coordinates. In this embodiment, the neural network model is a feed-forward neural network. When predicting the compensated coordinates, the connection point coordinates of the unconnected polyhedral space model are input, and after the hidden layer learns the relationship between the connection point coordinates of the unconnected polyhedral space model and the compensated coordinates, the predicted compensated coordinates are output in the output layer.

[0057] Load analysis module: Apply a first load and a second load at the connection points of two adjacent polyhedral space models, obtain the deformation parameters of the connection points, and determine the stability level of the modular building based on the deformation parameters. Since the connection points of the polyhedral space model are the key parts of the modular building, the design and construction thereof are relatively difficult. In addition to bearing the deadweight of the polyhedral space model, the connection points may also bear wind loads and earthquake loads during later use. Therefore, in this embodiment, in order to ensure the strength of the entire building, the first load is the wind load, and the second load is the earthquake load. The calculation process of the wind load is as follows:

[0058] w k =β z ×μ z ×μ s × o

[0059] Among them, w k is the wind load, β z is the gust coefficient of instantaneous wind pressure, μ z is the wind pressure height variation coefficient, μ s is the wind load shape factor, w o is the basic wind pressure; the values ​​are taken in accordance with the Code for Loads on Building Structures;

[0060] The calculation process of the seismic load is:

[0061] q=ρ E ×α max ×G

[0062] Where q is the seismic load, ρ E is the power amplification factor, α max The maximum value of the horizontal earthquake influence coefficient, G polyhedral space model is the standard value of the gravity load. In this embodiment, ρ E The value is 5.0, and the maximum value of the horizontal earthquake influence coefficient is determined according to the corresponding design intensity.

[0063] The load analysis module determines the stability level of the modular building through a stability level model; the construction process of the stability level model is: a large number of wind load-deformation number pairs and seismic load-deformation number pairs of different levels are obtained and marked by artificial experts; after marking, the wind load-deformation number pairs and seismic load-deformation number pairs are input into different neural network units in turn for iterative training; two neural network units are combined to obtain the deformation at the connection point of the polyhedron space model under different wind loads and seismic loads; the combination process of the two neural network units is: the output result of the first neural network unit after iterative training is input into the second neural network unit together with the seismic load, and finally the deformation at the connection point of the polyhedron space model under different wind loads and seismic loads is output.

[0064] A deformation threshold and a modular building stability grade corresponding to the deformation threshold are set to obtain a stability grade model that outputs the modular building stability grade based on the deformation; the wind load-deformation number pair includes different wind loads and the deformations at the connection points of the polyhedron space model corresponding to the different wind loads; the seismic load-deformation number pair includes different seismic loads and the deformations at the connection points of the polyhedron space model corresponding to the different seismic loads. In the design stage, the present invention simulates wind loads and seismic loads in the form of external loads to monitor the deformations at the connection points of the polyhedron space model, outputs the modular building stability grade through a neural network model, and ensures the strength of the modular building.

[0065] Example 2

[0066] This embodiment uses the modular energy-saving building design system of Embodiment 1 to perform modular energy-saving building design, including the following steps:

[0067] Obtain modular building project planning requirements and set constraints based on the requirements;

[0068] Construct a 3D model of the modular building based on the constraints to form the main body of the visual model;

[0069] Selecting a passive energy-saving constraint or an active energy-saving constraint to optimize the three-dimensional model based on the modular building project plan; the passive energy-saving constraint is to achieve energy saving through the building design itself, and the active energy-saving constraint is to achieve energy saving through external energy;

[0070] Dividing the three-dimensional model into a plurality of polyhedral space models based on the functional space, each of the polyhedral space models is highlighted on the visualization model body;

[0071] Determine the connection sequence of each polyhedral space model and label each polyhedral space model based on the connection sequence, obtain the connection point coordinates of each polyhedral space model, and optimize the connection point coordinates of the next polyhedral space model in real time based on the previous polyhedral space model;

[0072] A first load and a second load are applied at the connection points of two adjacent polyhedral space models, deformation parameters of the connection points are obtained, and the stability level of the modular building is determined based on the deformation parameters; the first load is a wind load, and the second load is an earthquake load.

[0073] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A modular energy-saving building design system, characterized in that: include: Parameter constraint module: used to obtain modular building project planning requirements and set constraints based on the requirements; Model building module: build a 3D model of modular buildings based on constraints to form a visual model body; An energy-saving constraint module, which selects a passive energy-saving constraint or an active energy-saving constraint to optimize the three-dimensional model based on the modular building project plan; the passive energy-saving constraint is to achieve energy saving through the building design itself, and the active energy-saving constraint is to achieve energy saving through external energy; Splitting module: used for dividing the three-dimensional model into a plurality of polyhedral space models based on the functional space, and each of the polyhedral space models is highlighted on the main body of the visualization model; Positioning module: used to determine the connection sequence of each polyhedral space model and label each polyhedral space model based on the connection sequence, and obtain the connection point coordinates of each polyhedral space model, and optimize the connection point coordinates of the next polyhedral space model in real time based on the previous polyhedral space model; Load analysis module: applying a first load and a second load at the connection points of two adjacent polyhedral space models, obtaining deformation parameters of the connection points, and determining the stability level of the modular building based on the deformation parameters.

2. A modular energy-saving building design system according to claim 1, characterized in that: The model building module includes a pre-definition unit, an instruction calling unit and a three-dimensional model building unit; The predefined unit defines a plurality of generation instructions based on a general specification for architectural design, each of the generation instructions includes a dialog box for inputting a restriction condition, and each generation instruction generates a standardized building unit model based on the restriction condition; The instruction calling unit is used to select and call the standardized building unit model; The three-dimensional model building unit is used to build a three-dimensional model of a modular building.

3. A modular energy-saving building design system according to claim 2, characterized in that: The model building module also includes a sharing unit, which is communicatively connected with a plurality of user terminals and is used for sharing the generation instruction.

4. A modular energy-saving building design system according to claim 3, characterized in that: The model building module also includes a permission setting unit, which is used to limit any one of the users to the main control terminal in a predefined manner when operating on users with different identities at the same time, and users with other identities are defaulted to auxiliary terminals. At the same time, the operation permission scope of the main control terminal and the auxiliary terminal is determined separately according to the identity limitations.

5. A modular energy-saving building design system according to claim 4, characterized in that: The splitting module is a splitting decision model based on a neural network. The calibrated functional splitting rules are input into the neural network tool, and iterative training is performed under the set training resources to form the splitting decision model. The three-dimensional model is used as the input of the splitting decision model, and the splitting decision model outputs multiple polyhedral space models after splitting.

6. A modular energy-saving building design system according to claim 5, characterized in that: The positioning module optimizes the connection point coordinates of the polyhedron space model in real time through a coordinate optimization model; The construction process of the coordinate optimization model is: The coordinates of the connection points of two adjacent polyhedral space models after connection are compared with the coordinates before connection and marked by manual experts. The coordinate difference of the connection points of two adjacent polyhedral space models after connection is obtained and coordinate compensation is set. The coordinates of the connection points of the unconnected polyhedral space models are input into the neural network model in sequence according to the time series number for coordinate compensation and the compensated coordinates are output.

7. A modular energy-saving building design system according to claim 6, characterized in that: The first load is a wind load, the second load is an earthquake load, and the calculation process of the wind load is: w k =b z ×m z ×m s ×w o Among them, w k is the wind load, β z is the gust coefficient of instantaneous wind pressure, μ z is the wind pressure height variation coefficient, μ s is the wind load shape factor, w o is the basic wind pressure; The calculation process of the seismic load is: q=ρ E ×a max ×G Where q is the seismic load, ρ E is the power amplification factor, α max The maximum value of the horizontal seismic influence coefficient and the G polyhedral space model are the standard values ​​of the gravity load.

8. A modular energy-saving building design system according to claim 7, characterized in that: The load analysis module determines the stability level of the modular building through a stability level model; The construction process of the stability level model is as follows: A large number of wind load-deformation pairs and seismic load-deformation pairs of different levels are obtained and marked by artificial experts; after marking, the wind load-deformation pairs and seismic load-deformation pairs are sequentially input into different neural network units for iterative training; two neural network units are combined to obtain the deformation at the connection point of the polyhedron space model under different wind loads and seismic loads; Setting a deformation value threshold and a modular building stability grade corresponding to the deformation value threshold, and obtaining a stability grade model for outputting the modular building stability grade based on the deformation value; The wind load-deformation number pairs include different wind loads and deformations at the connection points of the polyhedron space model corresponding to the different wind loads; The seismic load-deformation number pairs include different seismic loads and deformations at connection points of the polyhedron space model corresponding to the different seismic loads.

9. A modular energy-saving building design method, characterized in that: A modular energy-saving building design system according to any one of claims 1 to 8 is used, comprising the following steps: Obtain modular building project planning requirements and set constraints based on the requirements; Construct a 3D model of the modular building based on the constraints to form the main body of the visual model; Selecting a passive energy-saving constraint or an active energy-saving constraint to optimize the three-dimensional model based on the modular building project plan; the passive energy-saving constraint is to achieve energy saving through the building design itself, and the active energy-saving constraint is to achieve energy saving through external energy; Dividing the three-dimensional model into a plurality of polyhedral space models based on the functional space, each of the polyhedral space models is highlighted on the visualization model body; Determine the connection sequence of each polyhedral space model and label each polyhedral space model based on the connection sequence, obtain the connection point coordinates of each polyhedral space model, and optimize the connection point coordinates of the next polyhedral space model in real time based on the previous polyhedral space model; A first load and a second load are applied at the connection points of two adjacent polyhedral space models, deformation parameters of the connection points are obtained, and the stability level of the modular building is determined based on the deformation parameters; the first load is a wind load, and the second load is an earthquake load.

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