Space simulation interaction method and system based on space structure node optimization

Abstract

The invention provides a space simulation interaction method and system based on space structure node optimization, and the method comprises the steps: obtaining space structure data from source data according to a first operation instruction, and carrying out the data preprocessing of the space structure data; key feature points in the spatial structure data are extracted to serve as first spatial structure nodes; constructing a topological optimization mathematical model, performing node optimization on the first space structure nodes by using the topological optimization mathematical model to obtain second space structure nodes, and constructing a space simulation interaction scene based on the second space structure nodes; interaction elements are added in the space simulation interaction scene, interaction information sent by interaction equipment corresponding to the interaction elements is obtained, the state of the second space structure node is updated in real time according to the interaction information, and the space simulation interaction scene is updated according to the updated second space structure node. The technical problems that indoor building space simulation interaction is difficult, the use threshold is high and the interaction effect is poor in the prior art can be solved.

Description

Technical Field

[0001] The present invention relates to the field of spatial design system interaction technology, and in particular to a spatial simulation interaction method and system based on spatial structure node optimization. Background Art

[0002] With the continuous development of the construction industry and the increasing requirements for the quality of living and use space, it is becoming increasingly important to accurately present the interior space effect and achieve effective interactive experience during the architectural design stage. Although traditional two-dimensional architectural drawings can convey basic information such as size and layout, it is difficult for non-professionals (such as owners, ordinary users, etc.) to understand them. It is difficult to intuitively imagine the actual space experience after construction, including space scale, lighting, sight relationship, and interaction between different functional areas.

[0003] The emergence of computer-aided design (CAD) software has improved this situation to a certain extent. It can display indoor architectural space in the form of a three-dimensional model, making the spatial form more concrete. However, early CAD three-dimensional models were mostly static presentations, and users could only passively view preset angles and effects. They lacked interactivity and could not adjust elements in the space in real time according to their own ideas, such as furniture layout, decoration style, and space color, making it difficult to meet diverse needs and requirements for in-depth experience.

[0004] Commonly used 3D modeling software such as 3ds Max and SketchUp are also constantly improving their interactive functions. For example, some plug-ins or built-in functional modules are added to allow users to rotate, zoom, translate and other viewing operations on the model through mouse and keyboard operations. They are widely used in the early stage of project communication and modification in the fields of architectural design and interior design.

[0005] The operation of these software is still relatively complicated, requiring users to have certain professional software operation knowledge. For ordinary owners and end users without professional design background, it is difficult to get started, which is not conducive to the participation of a wide range of users in space design and simulation interaction. Moreover, their interactive feedback is more based on the visual changes of the software interface, lacking multi-sensory interactive experience such as touch and force feedback in the real physical environment, and is not real and comprehensive enough.

[0006] From a market perspective, whether it is an architectural design company that wants to better communicate design plans with customers and obtain feedback to optimize the design, or a real estate developer that wants to show homebuyers the interior space of a future house more vividly, or an ordinary family that wants to experience different decoration styles and space layout effects in advance when decorating, there is an urgent need for a relatively low-cost, simple and convenient operation, rich interactive experience and realistic indoor architectural space simulation interaction method. The spatial structure nodes that need to be adjusted must meet certain design standards, so that users from different backgrounds can easily participate in the space simulation, design and experience process to meet the diverse and personalized market needs. Summary of the invention

[0007] The purpose of the present invention is to overcome the above technical deficiencies and provide a spatial simulation interaction method based on spatial structure node optimization to solve the technical problems in the prior art of difficult indoor architectural space simulation interaction, high usage threshold and poor interaction effect.

[0008] In order to achieve the above technical objectives, in a first aspect, the technical solution of the present invention provides a spatial simulation interaction method based on spatial structure node optimization, comprising the following steps:

[0009] According to the first operation instruction, spatial structure data is acquired from source data, and data preprocessing is performed on the spatial structure data;

[0010] Extracting key feature points in the spatial structure data as first spatial structure nodes;

[0011] Constructing a topology optimization mathematical model, using the topology optimization mathematical model to perform node optimization on the first spatial structure node to obtain a second spatial structure node, and constructing a spatial simulation interaction scene based on the second spatial structure node;

[0012] An interactive element is added to the spatial simulation interactive scene, interactive information sent by an interactive device corresponding to the interactive element is obtained, the state of the second spatial structure node is updated in real time according to the interactive information, and the spatial simulation interactive scene is updated.

[0013] Compared with the prior art, the space simulation interaction method based on space structure node optimization of the present invention has the following beneficial effects:

[0014] Traditional spatial construction methods rely on the experience and intuition of designers and have many defects, such as difficulty in meeting user needs, low design efficiency, high cost, and difficult quality assurance. The spatial simulation interaction method based on spatial structure node optimization provided by the technical solution of the present invention can intelligently optimize the spatial structure nodes on the premise of meeting the design goals by constructing a topological optimization mathematical model, and construct a spatial simulation interaction scene based on the optimized spatial structure nodes. In addition, interactive elements are added to the spatial simulation interaction scene, and the interactive information sent by the interactive device corresponding to the interactive element is obtained. The state of the second spatial structure node is updated in real time according to the interactive information and the spatial simulation interaction scene is updated. For communication between architectural designers and customers, this accurate and real-time interactive spatial simulation method can enable designers to more intuitively show design concepts and spatial effects to customers. Customers can also make modifications on the spot and see real-time changes, avoiding communication barriers caused by inconsistent understanding of two-dimensional drawings or unclear verbal descriptions between the two parties, and promoting the two parties to reach a better design consensus.

[0015] During the decision-making process of a construction project (such as determining the decoration plan, adjusting the spatial functional layout, etc.), relevant decision makers can use this simulated interactive method to repeatedly try different space configurations, and evaluate the pros and cons of different plans based on intuitive interactive experience, so as to make more scientific and reasonable decisions and reduce the cost of later changes caused by design errors or non-compliance with actual usage needs.

[0016] According to some embodiments of the present invention, the constructing of a topology optimization mathematical model and using the topology optimization mathematical model to perform node optimization on the first spatial structure node to obtain a second spatial structure node includes:

[0017] An initial model is constructed to define an optimization problem, wherein the optimization problem includes: design variables, a design objective function, and a design response requiring constraints;

[0018] Perform sensitivity analysis according to the design response and the design variables to obtain sensitivity information;

[0019] Expanding the design response using the sensitivity information to create an approximate model based on the expanded design response, the design variables, the design objective function, and the initial model;

[0020] The design variables are updated based on the approximate model to obtain updated variables, and whether the updated variables reach the design target is determined according to the design target function; if the target is not reached, the updated variables are updated based on the approximate model until the updated variables reach the design target;

[0021] The approximate model that achieves the design goal is used as the topology optimization mathematical model, and the first spatial structure nodes are optimized according to the topology optimization mathematical model to obtain the second spatial structure nodes.

[0022] In the step of constructing the mathematical model of topological optimization, the optimization problem can be customized to meet different needs, and the optimization problem can be automatically matched and generated according to the source data. Then, the required optimization problem can be selected according to the actual needs, further improving the degree of intelligence. The design response that needs to be constrained can be the constraint on the deformation and stress level of the product during operation; the sensitivity information reflects the sensitivity of the design response (such as the strain energy, stress, displacement, etc. of the structure) to the change of the design variables (such as node coordinates, material parameters, etc.). By analyzing the sensitivity, it can be clear which design variables have a greater impact on the structural performance and which have a smaller impact; directly optimizing the complex finite element model often requires a lot of computing resources and time. The sensitivity information provides a basis for building an approximate model. By using the Taylor expansion and other approximate methods of the design response at a certain reference point of the design variable, the sensitivity is used as the coefficient of the expansion formula to establish an approximate relationship model between the design response and the design variable. The approximate model can replace the original finite element model for optimization calculation to a certain extent, greatly reducing the calculation workload, while maintaining a certain calculation accuracy; according to the mathematical model of topological optimization, the node of the first spatial structure is optimized to obtain the second spatial structure node. After using the model, the operation speed is improved to make the interaction smoother and the simulated interaction effect more accurate.

[0023] According to some embodiments of the present invention, the design objective function is expressed as:

[0024] Minimize→f(X)=f(x 1 ,x 2 ,x 3 …,x n )

[0025] The design response is expressed as:

[0026]

[0027] Where X = x 1 ,x 2 ,x 3 …,x n is the design variable, f(X) is the design target, g j (X) and h k (X) are the two constraints of the design response, and m represents the constraint g j (X) number, n represents the constraint h k(X) is the number of vectors, L is the initial vector, and U is the displacement vector.

[0028] According to some embodiments of the present invention, performing sensitivity analysis according to the design response and the design variable to obtain sensitivity information comprises the steps of:

[0029] Calculating the partial derivative of the design response with respect to the design variable and using it as the sensitivity information;

[0030] Among them, for the finite element equation, we have: |K|{U}={P}

[0031] |K| represents the stiffness matrix, {U} represents the displacement of each node in the structure after being subjected to force, and {P} represents the node load vector. Taking the partial derivatives of the design variable X on both sides, we get:

[0032]

[0033] Then the partial derivative of the displacement vector U is:

[0034]

[0035] The design response is a function of the displacement vector U:

[0036] g={Q} T {U}

[0037] g is the design response, Q is the design load vector;

[0038] The partial derivative of the design response with respect to the design variable is:

[0039]

[0040] According to some embodiments of the present invention, the step of expanding the design response using the sensitivity information to create an approximate model based on the expanded design response, the design variables, the design objective function, and the initial model includes:

[0041] expanding the design response according to the sensitivity information;

[0042] Using a preset approximation method, an explicit approximation model is obtained and iterated according to the expanded design response, the design variable, the design objective function and the initial model, wherein the approximation method includes any one of a linear approximation method, an inverse approximation method and a convex approximation method;

[0043] The explicit approximation model that has completed iteration is used as the approximate model.

[0044] Advantages of using explicit approximation models: Explicit approximation models usually do not require iterative solutions. For example, in structural optimization, the response surface method (RSM) based on explicit models can directly calculate the results through formulas without the need for complex iterative calculations like implicit methods. This greatly reduces the calculation time, especially when dealing with large-scale problems; for some problems in finite element analysis, explicit time integration algorithms (such as the central difference method) can directly calculate the displacement and velocity of the node in each time step without solving large linear equations, which makes the calculation faster. Since there is no need for complex iterative processes, explicit approximation models have relatively low requirements for computer memory, which is particularly important when dealing with large data sets or complex systems. For example, some explicit regression models in machine learning (such as linear regression) have a simple calculation process and do not require a large amount of memory to store intermediate results.

[0045] According to some embodiments of the present invention, the source data includes, but is not limited to: computer-aided design models, three-dimensional scanning data;

[0046] The data preprocessing of the spatial structure data comprises the following steps:

[0047] The source data is subjected to denoising and alignment processing, a filtering algorithm is used to remove environmental noise points in the source data, and the source data is processed through a feature matching algorithm.

[0048] The present invention can process different types of source data, that is, it can simultaneously extract key feature points of different types of source data as the first spatial structure nodes to participate in the calculation together, so there is no need to calculate the key feature points of different types of source data separately, which makes the method have a wide range of adaptation and high efficiency.

[0049] According to some embodiments of the present invention, extracting key feature points in the spatial structure data as first spatial structure nodes comprises the steps of:

[0050] In the case where the extraction setting information is not preset, obtaining the extraction setting information according to the spatial structure data;

[0051] According to the extraction setting information, the corner points, intersection points, boundary points of objects in the spatial structure data, the connection points of beams and columns, and the turning points of walls are extracted as the first spatial structure nodes, and attribute information is assigned to each of the first spatial structure nodes, wherein the attribute information includes: node type, the object to which it belongs, and material characteristics.

[0052] The present invention can preset the extraction setting information in advance to determine which key feature points should be extracted, thereby improving flexibility. If the user does not specify, it will be automatically generated according to the spatial structure data, so the degree of intelligence is improved. For example, in order to improve the calculation speed, some key feature points may be ignored in subsequent calculations. For example, two key feature points that are very close can be merged into one for calculation. Then, it can be determined whether they should be merged based on the extraction setting information. If the extraction setting information is set for the orientation of calculation speed, they can be merged. If it is for the orientation of calculation accuracy, the detailed information of the key feature points is retained.

[0053] According to some embodiments of the present invention, updating the state of the second spatial structure node in real time according to the interaction information and updating the spatial simulation interaction scene according to the updated second spatial structure node comprises the steps of:

[0054] Update the position of the second spatial structure node and the attribute information based on the interaction information;

[0055] Perform node optimization on the second spatial structure nodes using the topology optimization mathematical model;

[0056] The spatial simulation interaction scene is updated according to the updated second spatial structure node.

[0057] In the present invention, each interactive element of the same spatial simulation scene can correspond to multiple different interactive devices, so that different interactive devices can interact with the scene at the same time and present corresponding interactive effects; that is, the scene can be operated by multiple devices at the same time, and different interactive effects can be presented for each device in response to the operation of different devices.

[0058] In a second aspect, the technical solution of the present invention provides a spatial simulation interaction system based on spatial structure node optimization, comprising:

[0059] A data management module, used to obtain spatial structure data from multiple data sources, perform data preprocessing on the spatial structure data, and extract key feature points in the spatial structure data as first spatial structure nodes;

[0060] An optimization calculation module is used to construct a topology optimization mathematical model, use the topology optimization mathematical model to perform node optimization on the spatial structure nodes, and construct a spatial simulation interaction scene based on the optimized second spatial structure nodes;

[0061] An interactive control module adds interactive elements to the spatial simulation interactive scene, obtains interactive information sent by an interactive device corresponding to the interactive element, updates the state of the second spatial structure node in real time according to the interactive information, and updates the spatial simulation interactive scene according to the updated second spatial structure node.

[0062] In a third aspect, the technical solution of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute a spatial simulation interaction method based on spatial structure node optimization as described in any one of the first aspects.

[0063] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, wherein the abstract drawings are identical to one of the drawings in the specification:

[0065] Figure 1 A flowchart of a spatial simulation interaction method based on spatial structure node optimization provided by an embodiment of the present invention;

[0066] Figure 2 A flowchart of a spatial simulation interaction method based on spatial structure node optimization provided by another embodiment of the present invention. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0068] It should be noted that, although the functional modules are divided in the system schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0069] Reference Figure 1 , Figure 1 A flowchart of a spatial simulation interaction method based on spatial structure node optimization provided by one embodiment of the present invention.

[0070] The spatial simulation interaction method based on spatial structure node optimization includes but is not limited to the following steps:

[0071] Step S110, acquiring spatial structure data from source data according to the first operation instruction, and performing data preprocessing on the spatial structure data;

[0072] Step S120, extracting key feature points in the spatial structure data as first spatial structure nodes;

[0073] Step S130, constructing a topology optimization mathematical model, using the topology optimization mathematical model to perform node optimization on the first spatial structure node to obtain a second spatial structure node, and constructing a spatial simulation interaction scene based on the second spatial structure node;

[0074] Step S140, adding an interactive element to the spatial simulation interactive scene, obtaining interactive information sent by the interactive device corresponding to the interactive element, updating the state of the second spatial structure node in real time according to the interactive information, and updating the spatial simulation interactive scene according to the updated second spatial structure node.

[0075] In some embodiments, a spatial simulation interaction method based on spatial structure node optimization includes the following steps: according to a first operation instruction, obtaining spatial structure data from source data, and performing data preprocessing on the spatial structure data; extracting key feature points in the spatial structure data as the first spatial structure node; constructing a topology optimization mathematical model, using the topology optimization mathematical model to perform node optimization on the first spatial structure node to obtain a second spatial structure node, and constructing a spatial simulation interaction scene based on the second spatial structure node; adding interactive elements to the spatial simulation interaction scene, obtaining interactive information sent by the interactive device corresponding to the interactive element, and updating the status of the second spatial structure node in real time according to the interactive information and updating the spatial simulation interaction scene.

[0076] First, spatial structure data is acquired from source data. Spatial structure data is acquired from a variety of data sources, such as computer-aided design models, three-dimensional scanning data, model data in building information modeling systems, etc. These are also several common ways of acquiring source data in the field of spatial design technology. After the spatial structure data is collected, it is necessary to perform data preprocessing on the spatial structure data, such as denoising, alignment, and the like; then, the key feature points in the spatial structure data are selected as the first spatial structure node. It can be understood that the first spatial structure node, as the initial spatial structure node, has not been verified by the design standards.

[0077] Next, a topology optimization mathematical model is constructed, and the first spatial structure node is optimized using the topology optimization mathematical model to obtain the second spatial structure node. The topology optimization mathematical model sets the design objectives, design variables, and design constraints. In the spatial structure topology optimization, maximizing stiffness or minimizing flexibility is one of the main goals. For example, when performing topology optimization calculations in HyperWorks software using the OptiStruct solver, the goal is to optimize the stiffness of the structure while satisfying constraints such as the structural volume fraction, thereby ensuring that the structure can maintain good stability and load-bearing capacity when subjected to stress. This helps to build a sturdy and high-performance spatial structure in environmental art design to meet the mechanical requirements of actual use; the design constraints are mainly constraints on product deformation and stress levels during operation; and a spatial simulation interaction scene is constructed based on the second spatial structure node.

[0078] In the spatial simulation interaction scene constructed at the second spatial structure node, during the decision-making process of the construction project (such as determining the decoration plan, adjusting the spatial functional layout, etc.), relevant decision makers can repeatedly try different spatial configurations through this simulation interaction method, and evaluate the pros and cons of different plans based on intuitive interactive experience, so as to make more scientific and reasonable decisions and reduce the cost of later changes caused by design errors or failure to meet actual usage needs.

[0079] In summary, the spatial simulation interaction method based on spatial structure node optimization has significant beneficial effects in many aspects such as spatial presentation, interactive experience, cost control and design decision-making, and is expected to bring more efficient, high-quality and easy-to-use solutions to the field of indoor architectural space simulation interaction. However, the specific beneficial effects still need to be further considered and verified in combination with factors such as actual application scenarios and comparative reference technologies.

[0080] Reference Figure 2 , Figure 2 A flowchart of a spatial simulation interaction method based on spatial structure node optimization provided by another embodiment of the present invention.

[0081] Building a topology optimization mathematical model includes but is not limited to the following steps:

[0082] Step S210, constructing an initial model and defining an optimization problem, wherein the optimization problem includes: design variables, design objective functions, and design responses that require constraints;

[0083] Step S220, performing sensitivity analysis according to the design response and the design variables to obtain sensitivity information;

[0084] Step S230, expanding the design response using the sensitivity information to create an approximate model based on the expanded design response, design variables, design objective function and the initial model;

[0085] Step S240, updating the design variables based on the approximate model to obtain updated variables, and judging whether the updated variables reach the design target according to the design target function, if not, updating the updated variables based on the approximate model until the updated variables reach the design target;

[0086] Step S250: taking the approximate model that achieves the design goal as a topology optimization mathematical model, and performing node optimization on the first spatial structure node according to the topology optimization mathematical model to obtain a second spatial structure node.

[0087] In one embodiment, a spatial simulation interaction method based on spatial structure node optimization includes the following steps: according to a first operation instruction, obtaining spatial structure data from source data, and performing data preprocessing on the spatial structure data; extracting key feature points in the spatial structure data as a first spatial structure node; constructing a topology optimization mathematical model, using the topology optimization mathematical model to perform node optimization on the first spatial structure node to obtain a second spatial structure node, and constructing a spatial simulation interaction scene based on the second spatial structure node; adding interactive elements to the spatial simulation interaction scene, obtaining interactive information sent by the interactive device corresponding to the interactive element, and updating the status of the second spatial structure node in real time according to the interactive information and updating the spatial simulation interaction scene.

[0088] A topology optimization mathematical model is constructed, and the first spatial structure node is optimized using the topology optimization mathematical model to obtain a second spatial structure node, including: constructing an initial model, defining an optimization problem, and the optimization problem includes: design variables, design objective functions, and design responses that need to be constrained; performing sensitivity analysis based on the design responses and design variables to obtain sensitivity information; using the sensitivity information to expand the design response to create an approximate model based on the expanded design response, design variables, design objective functions, and the initial model; updating the design variables based on the approximate model to obtain updated variables, and judging whether the updated variables reach the design goals based on the design objective function, if the goals are not reached, updating the updated variables based on the approximate model until the updated variables reach the design goals; using the approximate model that reaches the design goals as a topology optimization mathematical model, and performing node optimization on the first spatial structure node based on the topology optimization mathematical model to obtain a second spatial structure node.

[0089] Performing sensitivity analysis based on design responses and design variables to obtain sensitivity information has beneficial effects:

[0090] Variable importance judgment: Sensitivity information reflects the sensitivity of the design response (such as the strain energy, stress, displacement, etc. of the structure) to the change of design variables (such as node coordinates, material parameters, etc.). By analyzing the sensitivity, it is possible to clarify which design variables have a greater impact on the structural performance and which have a smaller impact. For example, if a small change in a node coordinate causes a significant change in the total strain energy of the structure, then the node coordinate is a highly sensitive variable. During the optimization process, designers can focus on and prioritize the adjustment of these highly sensitive variables, thereby more effectively improving structural performance, determining the key direction of optimization, avoiding blind adjustment of design variables, and improving optimization efficiency.

[0091] Optimization strategy formulation: Based on the results of sensitivity analysis, targeted optimization strategies can be formulated. For design variables that contribute greatly to the improvement of structural performance, more radical adjustments can be adopted, such as making larger changes within their feasible range to quickly obtain significant improvements in structural performance; for variables with lower sensitivity, their optimization process can be appropriately simplified, or, provided that other constraints are met, they can be used as secondary optimization objects. This can reasonably allocate optimization resources, make the optimization process more targeted, and improve the overall optimization effect.

[0092] Model simplification and accelerated calculation: Direct optimization calculation of complex finite element models often requires a lot of computing resources and time. Sensitivity information provides a basis for building an approximate model. By using approximate methods such as Taylor expansion of the design response at a reference point of the design variable, and using sensitivity as the coefficient of the expansion, an approximate relationship model between the design response and the design variable is established. This approximate model can replace the original finite element model for optimization calculation to a certain extent, greatly reducing the calculation workload while maintaining a certain calculation accuracy. For example, in the process of multiple iterative optimization, the approximate model based on sensitivity information can quickly evaluate the structural performance under different design variable values ​​without the need for a complete finite element analysis each time, which significantly improves the optimization calculation speed and makes the optimization design of complex structures feasible in practical engineering applications.

[0093] Iterative optimization convergence acceleration: During the iterative optimization process, the approximate model can more quickly predict the trend of structural performance changes under different combinations of design variables, thereby helping the optimization algorithm to find the optimal solution or the area close to the optimal solution more quickly. By continuously updating the approximate model so that it gradually approaches the actual structural performance response, the optimization process can converge along a more effective path, reduce the number of iterations, and further improve the optimization efficiency. At the same time, the approximate model can also update the sensitivity analysis during the optimization process, timely reflect the dynamic changes in the impact of design variable changes on structural performance, and provide more accurate guidance information for the optimization algorithm.

[0094] Furthermore, the design objective function is expressed as:

[0095] Minimize→f(X)=f(x 1 ,x 2 ,x 3 …,x n )

[0096] The design response is expressed as:

[0097]

[0098] Where X = x 1 ,x 2 ,x 3 …,x m is the design variable, f(X) is the design target, and h k (X) are the two constraints of the design response, and m represents the constraint g j (X) number, n represents the constraint h k (X) is the number of vectors, L is the initial vector, and U is the displacement vector.

[0099] in, It is the third constraint defined by the design variable X. n represents the number of design variables X. n is a positive integer, that is, the value range of n is n∈{1,2,3,…}.

[0100] In one embodiment, g k (X) represents the stress constraint in the structure, ensuring that the stress of the structure under a given load does not exceed the allowable stress of the material;

[0101] Specifically, under the constraint g k (X)≤0j=1,…,m, where m represents the inequality constraint g j (X), m is a positive integer whose value range is m∈{1,2,3,…}.

[0102] In one embodiment, h(X) represents the temperature constraint in thermal design.

[0103] Specifically, under the constraint h k (X)≤0k=1,…,m h Medium, m h represents the number of inequality constraints h(X), m h is a positive integer whose value range is m h ∈{1,2,3,…}.

[0104] Perform sensitivity analysis based on design responses and design variables to obtain sensitivity information, including the following steps:

[0105] Calculate the partial derivatives of the design response with respect to the design variables and use them as sensitivity information;

[0106] Among them, for the finite element equation, we have: |K|{U}={P}

[0107] |K| represents the stiffness matrix, {U} represents the displacement of each node in the structure after being subjected to force, and {P} represents the node load vector. Taking the partial derivatives of the design variable X on both sides, we get:

[0108]

[0109] Then the partial derivative of the displacement vector U is:

[0110]

[0111] The design response is a function of the displacement vector U:

[0112] g={Q} T {U}

[0113] g is the design response;

[0114] The partial derivative of the design response with respect to the design variable is:

[0115]

[0116] Directly using the above method to solve the problem is called a direct method. The direct method is suitable for optimization problems with many design constraints and few design variables, such as sensitivity solutions for shape optimization and size optimization. For optimization problems with few design constraints and many design variables, such as topology optimization and shape optimization, an adjoint variable E can be introduced in the calculation of sensitivity. The adjoint variable E satisfies the following points:

[0117] K|{E}={Q}

[0118] The partial derivatives of the design response with respect to the design variables are:

[0119]

[0120] In one embodiment, the design response is expanded using sensitivity information to create an approximate model based on the expanded design response, design variables, design objective function and initial model, including: expanding the design response according to the sensitivity information; using a preset approximation method to obtain an explicit approximation model based on the expanded design response, design variables, design objective function and initial model and iterating, wherein the approximation method includes any one of a linear approximation method, an inverse approximation method and a convex approximation method; and using the iterated explicit approximation model as the approximate model.

[0121] Direct optimization of the finite element model requires multiple finite element solutions at each iteration step, which is labor-intensive. In addition, the finite element model is implicit and must be explicitly approximated to create an approximate model. Sensitivity information is used to expand the design response to obtain an explicit approximation model. The approximation method is as follows:

[0122] Linear approximation:

[0123]

[0124] Inverse approximation:

[0125]

[0126] Convex approximation:

[0127]

[0128] when c ij =1, when

[0129] In some embodiments, a spatial simulation interaction method based on spatial structure node optimization includes the following steps: according to a first operation instruction, spatial structure data is obtained from source data, and data preprocessing of the spatial structure data is performed; key feature points in the spatial structure data are extracted as first spatial structure nodes; a topology optimization mathematical model is constructed, and the first spatial structure node is optimized using the topology optimization mathematical model to obtain a second spatial structure node, and a spatial simulation interaction scene is constructed based on the second spatial structure node; an interactive element is added to the spatial simulation interaction scene, and interactive information sent by an interactive device corresponding to the interactive element is obtained, and the state of the second spatial structure node is updated in real time according to the interactive information and the spatial simulation interaction scene is updated. The source data includes, but is not limited to, computer-aided design models, three-dimensional scanning data, and model data in a building information model system; data preprocessing of the spatial structure data includes the steps of: denoising and aligning the source data, using a filtering algorithm to remove environmental noise points in the source data, and processing the source data through a feature matching algorithm.

[0130] The processing of three-dimensional scanning data through feature matching algorithms generally includes feature matching based on distance measurement: 1. Euclidean distance, which calculates the Euclidean distance between two feature vectors (that is, the extended form of the straight-line distance between two points in space in multidimensional vector space). When matching features, a distance threshold is usually set. When the Euclidean distance between two features is less than the threshold, they are considered to be a pair of matching features. For example, for the descriptor vectors of two extracted point features, the square root of the sum of the squares of the differences in each corresponding dimension is calculated to obtain the Euclidean distance value, which is compared with the preset threshold to determine whether it matches. 2. Cosine similarity, which measures the cosine value of the angle between two feature vectors. The closer its value is to 1, the closer the directions of the two vectors are, which means the more similar the features are. In practical applications, a suitable similarity threshold can also be set to determine whether the features match. It is often used in feature vector matching scenarios based on directional information, such as the matching of local feature descriptors constructed based on normal directions.

[0131] In some embodiments, a spatial simulation interaction method based on spatial structure node optimization includes the following steps: according to a first operation instruction, obtaining spatial structure data from source data, and performing data preprocessing on the spatial structure data; extracting key feature points in the spatial structure data as the first spatial structure node; constructing a topology optimization mathematical model, using the topology optimization mathematical model to perform node optimization on the first spatial structure node to obtain a second spatial structure node, and constructing a spatial simulation interaction scene based on the second spatial structure node; adding interactive elements to the spatial simulation interaction scene, obtaining interactive information sent by the interactive device corresponding to the interactive element, and updating the status of the second spatial structure node in real time according to the interactive information and updating the spatial simulation interaction scene.

[0132] Extracting key feature points in the spatial structure data as the first spatial structure node includes the following steps:

[0133] In the case where the extraction setting information is not preset, the extraction setting information is obtained according to the spatial structure data;

[0134] According to the extraction setting information, the corner points, intersection points, boundary points of objects in the spatial structure data, the connection points of beams and columns, and the turning points of walls are extracted as the first spatial structure nodes, and attribute information is assigned to each first spatial structure node, and the attribute information includes: node type, object to which it belongs, and material characteristics.

[0135] The state of the second spatial structure node is updated in real time according to the interactive information, and the spatial simulation interactive scene is updated according to the updated second spatial structure node, including the steps of: updating the position and attribute information of the second spatial structure node based on the interactive information; performing node optimization on the second spatial structure node using a topological optimization mathematical model; and updating the spatial simulation interactive scene according to the updated second spatial structure node.

[0136] Adjusting the attribute information of the second spatial structure node based on the interactive information can realize real-time dynamic interaction. After the user operates the interactive device in the spatial simulation interactive scene (such as changing the position of furniture by dragging the mouse, adjusting the height of the wall with a handle, etc.) to generate interactive information, the attribute information of the second spatial structure node can be adjusted immediately, thereby making the entire spatial scene quickly change accordingly. This is just like when renovating the indoor space in real life, every action can immediately see the changes in the spatial layout and form, providing users with a real-time, smooth and highly immersive interactive experience, making users feel as if they are really in a real space that can be shaped at will, greatly enhancing the user's sense of participation and control.

[0137] Adjusting the attribute information of the second spatial structure node based on the interactive information can meet personalized needs. Different users have different ideas and personalized aesthetic and functional requirements for indoor architectural space. By flexibly adjusting the attribute information of the spatial structure node based on the interactive information, users can easily customize the space according to their own wishes, such as changing the color attributes of the room to create different atmospheres, adjusting the size and position of doors and windows to optimize the lighting and ventilation effects, and moving or changing the layout of furniture to meet specific usage habits. Whether it is a home user envisioning an ideal home environment or a commercial venue operator planning a unique functional zoning layout, both can be met in this way, so that each user can create a unique indoor space simulation effect.

[0138] Adjusting the attribute information of the second spatial structure node based on interactive information can accelerate design iteration optimization. For architects and interior designers, in the process of communicating design plans with customers or improving their own plans, they may need to spend a lot of time manually modifying model parameters and re-rendering scenes to show different effects. Now, with the help of the function of adjusting node attribute information based on interactive information, designers can quickly make adjustments based on the opinions of customers on site (for example, if a customer thinks a wall is too long and wants to shorten it, the designer will immediately change the length attribute of the corresponding spatial structure node through interactive operations), and instantly present a new spatial form, which greatly speeds up the speed of design iteration and helps to obtain a more optimized design plan in a shorter time.

[0139] Adjusting the attribute information of the second spatial structure node based on the interactive information can accurately obtain feedback information. By observing the user's operation process of adjusting the node attribute information according to their own ideas and the final spatial effect, the designer can more accurately obtain the user's feedback information on the space, such as preferences, functional requirements, and dissatisfaction. For example, if the user frequently adjusts the spatial size or functional layout of a certain area, it means that there may be some areas in the area that need to be improved or focused on in the user's mind. The designer can make targeted design adjustments based on this, thereby improving the quality of the design and making it more in line with the actual needs of the user.

[0140] In one embodiment, a spatial simulation interaction system based on spatial structure node optimization includes: a data management module, which is used to obtain spatial structure data from multiple data sources, perform data preprocessing on the spatial structure data, and extract key feature points in the spatial structure data as the first spatial structure node; an optimization calculation module, which is used to construct a topology optimization mathematical model, use the topology optimization mathematical model to optimize the spatial structure nodes, and construct a spatial simulation interaction scene based on the optimized second spatial structure node; an interaction control module, which adds interaction elements to the spatial simulation interaction scene, obtains interaction information sent by the interaction device corresponding to the interaction element, updates the status of the second spatial structure node in real time according to the interaction information, and updates the spatial simulation interaction scene according to the updated second spatial structure node.

[0141] The present invention can accurately simulate source data, obtain data from multiple data sources through the data management module and extract key feature points as the first spatial structure node, and can focus on the most representative and influential elements to build simulation scenes, avoid interference from irrelevant data, and make the subsequent constructed spatial simulation interaction scenes more in line with the actual spatial structure, thereby improving the accuracy of spatial simulation. For example, in architectural space simulation, accurate extraction of key beam and column structure node data can realistically restore the internal spatial layout and mechanics of the building.

[0142] The present invention has high optimization calculation efficiency. The optimization calculation module uses the topology optimization mathematical model to optimize the spatial structure nodes, and can quickly screen and adjust the nodes in a scientific and reasonable mathematical way. Compared with the traditional empirical or rough construction method, it greatly reduces unnecessary calculations and trial and error processes, and effectively improves the efficiency of constructing spatial simulation interactive scenes, so that the entire system can be put into use more quickly. For example, when simulating the internal spatial structure of complex machinery, the optimized node layout can be determined more quickly and the scene can be generated.

[0143] The present invention can respond to interactions in real time, and the interaction control module can update the status of the spatial structure nodes in real time according to the interaction information sent by the interaction device. This means that when the user interacts with the spatial simulation scene, such as controlling the movement of virtual objects or changing the spatial layout through a handle, the user can immediately see the corresponding changes, bringing a smooth and instant interactive experience, as if they are in a real controllable spatial environment. Situations such as real-time changes in terrain structure in a virtual game scene can make players feel more immersed.

[0144] The present invention can present rich interactive elements, add interactive elements to spatial simulation interactive scenes, and manage and update and store interactive data in real time with the help of data processing and feedback modules. It can support diverse interactive forms and rich virtual object state changes. For example, it can simulate the physical interaction effects (collision, friction, etc.) of objects of different materials in space, and can also display various visual effects such as light and shadow that change with the interaction, thereby comprehensively improving the user's interactive experience dimension.

[0145] The spatial simulation interaction system of the present invention manages data in an orderly manner. The data processing and feedback module is responsible for the processing and management of the data of the entire spatial simulation process, covering user interaction data and virtual object status data, etc., so that the flow and storage of data are in order, which is convenient for the subsequent review and analysis of the simulation process and further improvement and expansion of applications based on the data. For example, scientific researchers can review the data of each stage in the simulation experiment for in-depth research.

[0146] The spatial simulation interactive system of the present invention has the intuitiveness of visual feedback, and displays the changes of spatial structure nodes and interaction effect information in a visual manner, which allows users to more intuitively understand various abstract data and complex state changes in spatial simulation. Whether it is professionals viewing the changes in structural mechanics or ordinary users experiencing the visual changes brought about by the interaction, there is no need to interpret obscure data tables, etc., which reduces the cost of understanding and enhances the usability of the system.

[0147] The spatial simulation interactive system of the present invention has multi-field applicability: since it can obtain data from a variety of data sources and has multiple functions such as optimization and interaction, the system can be widely used in many fields such as architectural design (simulating the use and stress conditions of architectural space), game development (creating immersive interactive game scenes), industrial manufacturing (simulating the internal space assembly and operation of machinery), education and teaching (such as allowing students to intuitively experience physical space phenomena, etc.), providing powerful solutions for the space-related simulation needs of different industries.

[0148] The spatial simulation interactive system of the present invention can be flexibly expanded and upgraded: each module has a clear division of labor and orderly data management, which facilitates the subsequent flexible expansion and upgrading of the system according to new technologies (such as more advanced topology optimization algorithms, integration of new interactive device functions, etc.) and application scenario requirements. For example, new virtual reality equipment can be connected to further enhance the interactive immersion, or the functions of the data management module can be improved in combination with new data analysis methods, etc., to ensure the vitality and adaptability of the system.

[0149] As a non-transient computer-readable storage medium, the memory can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0150] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, and may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0151] In addition, an embodiment of the present invention also provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are executed by a processor or controller, for example, by a processor in the above-mentioned terminal embodiment, so that the above-mentioned processor can execute the spatial simulation interaction method based on spatial structure node optimization in the above-mentioned embodiment.

[0152] It will be appreciated by those skilled in the art that all or some of the steps and systems in the disclosed method above may be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that may be used to store desired information and may be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0153] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above-mentioned implementation mode. Technical personnel familiar with the field can also make various equivalent deformations or substitutions without violating the spirit of the present invention. These equivalent deformations or substitutions are all included in the scope defined by the claims of the present invention.

[0154] The above specific implementations of the present invention do not constitute a limitation on the protection scope of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A spatial simulation interaction method based on spatial structure node optimization, characterized in that: The following steps are involved: According to the first operation instruction, spatial structure data is acquired from source data, and data preprocessing is performed on the spatial structure data; Extracting key feature points in the spatial structure data as first spatial structure nodes; Constructing a topology optimization mathematical model, using the topology optimization mathematical model to perform node optimization on the first spatial structure node to obtain a second spatial structure node, and constructing a spatial simulation interaction scene based on the second spatial structure node; Add an interactive element to the spatial simulation interactive scene, obtain interactive information sent by the interactive device corresponding to the interactive element, update the state of the second spatial structure node in real time according to the interactive information, and update the spatial simulation interactive scene according to the updated second spatial structure node.

2. The spatial simulation interaction method based on spatial structure node optimization according to claim 1 is characterized in that: The constructing of the topology optimization mathematical model and using the topology optimization mathematical model to perform node optimization on the first spatial structure node to obtain the second spatial structure node includes: Constructing an initial model and defining an optimization problem, wherein the optimization problem includes: design variables, design objective functions, and design responses; Perform sensitivity analysis according to the design response and the design variables to obtain sensitivity information; Expanding the design response using the sensitivity information to create an approximate model based on the expanded design response, the design variables, the design objective function, and the initial model; The design variables are updated based on the approximate model to obtain updated variables, and whether the updated variables reach the design target is determined according to the design target function; if the design target is not reached, the updated variables are updated based on the approximate model until the updated variables reach the design target; The approximate model that achieves the design goal is used as the topology optimization mathematical model, and the first spatial structure nodes are optimized according to the topology optimization mathematical model to obtain the second spatial structure nodes.

3. The spatial simulation interaction method based on spatial structure node optimization according to claim 2 is characterized in that: The design objective function is expressed as: Minimize→f(X)=f(x1,x2,x3…,x n ) The design response is expressed as: Where X = x1, x2, x3…, x n is the design variable, f(X) is the design target, g j (X) and h k (X) are the two constraints of the design response, and m represents the constraint g j (X) number, n represents the constraint h k (X) is the number of vectors, L is the initial vector, and U is the displacement vector.

4. The spatial simulation interaction method based on spatial structure node optimization according to claim 3 is characterized in that: The step of performing sensitivity analysis according to the design response and the design variables to obtain sensitivity information comprises the following steps: Calculating the partial derivative of the design response with respect to the design variable and using it as the sensitivity information; Among them, for the finite element equation, we have: |K|{U}={P} |K| represents the stiffness matrix, {U} represents the displacement of each node in the structure after being subjected to force, and {P} represents the node load vector. Taking the partial derivatives of the design variable X on both sides, we get: Then the partial derivative of the displacement vector U is: The design response is a function of the displacement vector U: g={Q} T {U} g is the design response, Q is the design load vector; The partial derivative of the design response with respect to the design variable is:

5. The spatial simulation interaction method based on spatial structure node optimization according to claim 2 is characterized in that: The step of expanding the design response by using the sensitivity information to create an approximate model based on the expanded design response, the design variables, the design objective function, and the initial model comprises: expanding the design response according to the sensitivity information; Using a preset approximation method, an explicit approximation model is obtained and iterated according to the expanded design response, the design variable, the design objective function and the initial model, wherein the approximation method includes any one of a linear approximation method, an inverse approximation method and a convex approximation method; The explicit approximation model that has completed iteration is used as the approximate model.

6. The spatial simulation interaction method based on spatial structure node optimization according to claim 1 is characterized in that: The source data include but are not limited to: computer-aided design models, three-dimensional scanning data; The data preprocessing of the spatial structure data comprises the following steps: The source data is subjected to denoising and alignment processing, a filtering algorithm is used to remove environmental noise points in the source data, and the source data is processed through a feature matching algorithm.

7. The spatial simulation interaction method based on spatial structure node optimization according to claim 1 is characterized in that: Extracting key feature points in the spatial structure data as first spatial structure nodes comprises the steps of: In the case where the extraction setting information is not preset, obtaining the extraction setting information according to the spatial structure data; According to the extraction setting information, the corner points, intersection points, boundary points of objects in the spatial structure data, the connection points of beams and columns, and the turning points of walls are extracted as the first spatial structure nodes, and attribute information is assigned to each of the first spatial structure nodes, wherein the attribute information includes: node type, the object to which it belongs, and material characteristics.

8. The spatial simulation interaction method based on spatial structure node optimization according to claim 7 is characterized in that: The method of updating the state of the second spatial structure node in real time according to the interaction information and updating the spatial simulation interaction scene according to the updated second spatial structure node comprises the steps of: Update the position of the second spatial structure node and the attribute information based on the interaction information; Perform node optimization on the second spatial structure nodes using the topology optimization mathematical model; The spatial simulation interaction scene is updated according to the updated second spatial structure node.

9. A spatial simulation interactive system based on spatial structure node optimization, characterized in that: include: A data management module, used to obtain spatial structure data from multiple data sources, perform data preprocessing on the spatial structure data, and extract key feature points in the spatial structure data as first spatial structure nodes; An optimization calculation module is used to construct a topology optimization mathematical model, use the topology optimization mathematical model to perform node optimization on the spatial structure nodes, and construct a spatial simulation interaction scene based on the optimized second spatial structure nodes; An interactive control module adds interactive elements to the spatial simulation interactive scene, obtains interactive information sent by an interactive device corresponding to the interactive element, updates the state of the second spatial structure node in real time according to the interactive information, and updates the spatial simulation interactive scene according to the updated second spatial structure node.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the spatial simulation interaction method based on spatial structure node optimization as described in any one of claims 1 to 8.

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