A prefabricated building construction model construction method, system, medium and product

Abstract

A prefabricated building construction model construction method, system, medium and product, relate to the field of electric digital data processing, the method comprises the following steps: receiving a first prefabricated component placement instruction, generating a first prefabricated component node, and generating a first virtual placeholder node at the bottom boundary coordinates thereof to obtain an initial directed acyclic graph; receiving a second prefabricated component placement instruction, determining a matching component node; replacing the first virtual placeholder node with the matching component node and generating a second virtual placeholder node to obtain an updated directed acyclic graph; based on the component nodes in the updated directed acyclic graph, extracting lower component nodes to obtain adjacent component node pairs; constructing a space support tree and extracting a component node sequence to obtain a construction sequence time axis; extracting time sequence parameters and writing them into the corresponding component nodes in the updated directed acyclic graph to obtain a prefabricated building construction model. By implementing the present application, the work efficiency of constructing a prefabricated construction model from top to bottom can be improved.

Description

Technical Field

[0001] This application relates to the field of electronic digital data processing, and in particular to a method, system, medium and product for constructing prefabricated building construction models. Background Technology

[0002] Prefabricated buildings primarily consist of prefabricated components manufactured in factories, which are then assembled on-site. They are characterized by energy efficiency, environmental friendliness, and short construction cycles. Building Information Modeling (BIM) technology is widely used in the project management of prefabricated buildings. Engineers need to pre-build a complete three-dimensional construction model in the software system to guide actual construction processes such as component hoisting, node connection, and resource scheduling on-site.

[0003] The relevant technologies typically involve bottom-up model building. That is, the user must first place the foundational components (such as bottom-level load-bearing columns) on a virtual ground plane within the software. Then, when placing upper-level components (such as main beams), the system requires the user to explicitly select the existing bottom-level component as the host reference. The system's underlying data engine directly extracts the 3D coordinates and geometric elevation parameters of this host reference, using them as independent variables in the position calculation formula for the upper-level components. This renders the upper-level components in 3D space, and in this way, a rigid data dependency tree between components is established layer by layer upwards.

[0004] However, with the upgrading of architectural design concepts, engineers have developed new demands when conducting conceptual scheme simulations or special construction methods (such as reverse construction or modular overall lifting and hoisting) simulations. These demands include prioritizing the construction of top-suspended structures or constructing local spatial modules in a spanning manner. The relevant technologies often require the prefabrication of the bottom layer components first, and then the replacement or modification of the bottom layer components, resulting in low work efficiency. Summary of the Invention

[0005] This application provides a method, system, medium, and product for constructing prefabricated building construction models, which can improve the work efficiency when constructing prefabricated construction models from top to bottom.

[0006] In a first aspect, this application provides a method for constructing a prefabricated building construction model, applied to a construction simulation system. The method includes: receiving a first prefabricated component placement instruction; generating a first prefabricated component node corresponding to the first prefabricated component placement instruction in a three-dimensional virtual space; generating a first virtual occupant node at the bottom boundary coordinates of the first prefabricated component node to obtain an initial directed acyclic graph containing the first prefabricated component node and the first virtual occupant node; receiving a second prefabricated component placement instruction; performing a spatial intersection operation on the spatial coordinate region corresponding to the second prefabricated component placement instruction and the first virtual occupant node in the initial directed acyclic graph to obtain a matching component node; and replacing the first virtual occupant node in the initial directed acyclic graph with the matching component node. The system generates component nodes and creates a second virtual placeholder node at the bottom boundary coordinates of the matching component nodes to obtain an updated directed acyclic graph (DAG). Based on the component nodes in the updated DAG, geometrically intersecting test segments are generated along the gravity direction axis. Lower-level component nodes that coincide with the coordinates of the geometrically intersecting test segments are extracted to obtain pairs of adjacent component nodes with spatial connection relationships. A hierarchical mapping relationship between adjacent component node pairs is constructed to obtain a spatial support tree. A topological sorting algorithm is then applied to the spatial support tree to extract the component node sequence, resulting in a construction sequence timeline. The time series parameters in the construction sequence timeline are extracted and written into the corresponding component nodes in the updated DAG to obtain a prefabricated building construction model.

[0007] In the above embodiments, the construction simulation system adopts a mechanism of generating virtual occupant nodes at the bottom of prefabricated components and replacing nodes based on spatial intersection operations. Therefore, it can pre-establish the spatial subordination benchmark of the upper layer components when the bottom layer physical components are not placed. This effectively solves the rigid constraint problem in the prior art that the upper layer components can only be generated by relying on the bottom layer physical components, and thus realizes the flexible construction of the top-down suspended prefabricated building construction model.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, the step of generating a first virtual placeholder node at the bottom boundary coordinates of the first prefabricated component node to obtain an initial directed acyclic graph containing the first prefabricated component node and the first virtual placeholder node specifically includes: extracting the three-dimensional mesh model of the first prefabricated component node, obtaining the set of bottom vertices with the smallest Z-axis coordinate value in the three-dimensional mesh model; generating a two-dimensional bounding rectangle based on the extreme coordinates of the bottom vertex set to obtain the bottom boundary coordinates; generating a three-dimensional bounding box by combining the bottom boundary coordinates and a preset extension depth value to obtain the first virtual placeholder node; and writing the first prefabricated component node and the first virtual placeholder node into a memory graph structure to obtain the initial directed acyclic graph.

[0009] In the above embodiments, the construction simulation system uses the operation logic of extracting the bottom vertex set to generate a two-dimensional bounding rectangle and combining it with the extension depth to construct a three-dimensional bounding box. Therefore, it defines the effective bearing space range under the prefabricated component, effectively solving the problem of low accuracy of subsequent node matching caused by the fuzzy calculation of the component occupancy area in the prior art. This enables the accurate expression of virtual occupancy nodes in three-dimensional space and the writing of graph structure.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, the step of generating a two-dimensional bounding rectangle based on the extreme coordinates of the bottom vertex set to obtain the bottom boundary coordinates specifically includes: extracting the two-dimensional projected coordinates of the bottom vertex set; performing a convex hull algorithm on the two-dimensional projected coordinates to obtain a two-dimensional convex hull polygon; extracting each edge segment of the two-dimensional convex hull polygon; generating corresponding bounding rectangles with each edge segment as the reference direction to obtain multiple bounding rectangle sets; calculating the area value of each bounding rectangle in the multiple bounding rectangle sets; extracting the target bounding rectangle with the smallest area value to obtain the two-dimensional bounding rectangle; and extracting the corner coordinates of the two-dimensional bounding rectangle to obtain the bottom boundary coordinates.

[0011] In the above embodiments, the construction simulation system eliminates the interference of redundant vertices at the bottom of irregular components by executing the convex hull algorithm and the minimum area circumscribed rectangle extraction logic, thereby obtaining the most compact boundary coordinates and improving the accuracy of boundary calculation and space utilization.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, the step of generating geometrically intersecting test segments along the gravity direction axis, extracting lower-level component nodes whose coordinates coincide with the geometrically intersecting test segments, and obtaining adjacent component node pairs with spatial continuity specifically includes: extracting the bottom polygons of the component nodes in the updated directed acyclic graph, generating a two-dimensional sampling point array inside the bottom polygons; generating downward-extending rays along the gravity direction axis from each sampling point in the two-dimensional sampling point array as the starting point, obtaining multiple geometrically intersecting test segments; extracting a set of candidate component nodes whose coordinates coincide with the multiple geometrically intersecting test segments; extracting the target node with the largest Z-axis coordinate value from the candidate component node set, obtaining the lower-level component node; and combining the component node emitting the geometrically intersecting test segments with the lower-level component nodes to obtain adjacent component node pairs with spatial continuity.

[0013] In the above embodiments, the construction simulation system conducts intersection tests by emitting gravity direction rays through the bottom sampling point array, accurately capturing the physical support state between components, eliminating side nodes without actual support relationships, and ensuring the physical rationality of the spatial support tree construction.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, the step of extracting a set of candidate component nodes whose coordinates coincide with those of multiple geometrically intersecting test segments specifically includes: obtaining multiple initial collision nodes that are penetrated by multiple geometrically intersecting test segments, and extracting the structural attribute label of each initial collision node; when the structural attribute label is a non-load-bearing label, removing the corresponding initial collision node from the multiple initial collision nodes to obtain a set of candidate component nodes.

[0015] In the above embodiments, the construction simulation system introduces a structural attribute label filtering mechanism to eliminate decorative or non-load-bearing components after the ray collision test, ensuring that all extracted candidate component nodes have actual load-bearing capacity and improving the engineering rigor of the support relationship determination.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, the step of performing a topology sorting algorithm on the spatial support tree to extract the component node sequence and obtain the construction sequence timeline specifically includes: performing a topology sorting algorithm on the spatial support tree to obtain the longest path hop count from each component node in the spatial support tree to the root node, thereby obtaining a topology depth value; merging component nodes with the same topology depth value into the same array set to obtain a component node sequence containing multiple sets of parallel construction batches; and assigning an increasing timestamp parameter to each set of parallel construction batches in the component node sequence in descending order of topology depth value to obtain the construction sequence timeline.

[0017] In the above embodiments, the construction simulation system adopts a scheduling algorithm that calculates the topology depth based on the longest path hop count and merges parallel construction batches according to the depth. Therefore, it transforms the complex spatial support tree into a time series that can be executed in parallel, effectively solving the problem that the component installation sequence cannot adapt to spatial dependencies in the prior art. This enables the scientific arrangement of the construction time axis and the optimization of the parallel construction period.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, the step of assigning incremental timestamp parameters to each set of parallel construction batches in the component node sequence according to the decreasing order of topology depth values ​​to obtain the construction sequence timeline specifically includes: extracting the three-dimensional bounding boxes of all component nodes in the same set of parallel construction batches, performing an intersection operation on the three-dimensional bounding boxes to obtain the interference volume value; when the interference volume value is greater than zero, abstracting the component nodes in the set of parallel construction batches as vertices in the interference topology graph, and connecting the component nodes with interference volume values ​​greater than zero as undirected edges; performing a graph coloring algorithm on the interference topology graph to calculate the minimum number of color types required, and classifying the component nodes assigned the same color into independent sets of conflict-free sub-batches; and assigning continuously increasing timestamp parameters to each set of conflict-free sub-batches according to the decreasing order of topology depth values ​​to obtain the construction sequence timeline.

[0019] In the above embodiments, the construction simulation system identifies spatial conflicts within parallel batches by calculating bounding box interference volume and splits conflict-free batches, eliminating the potential for physical collisions at the same time point and ensuring the feasibility of the construction simulation sequence in actual operations.

[0020] In a second aspect, embodiments of this application provide a construction simulation system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, which includes computer instructions, and the one or more processors call the computer instructions to cause the construction simulation system to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a construction simulation system, cause the construction simulation system to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a construction simulation system, cause the construction simulation system to perform the method described in the first aspect and any possible implementation thereof.

[0023] Understandably, the construction simulation system provided in the second aspect, the computer storage medium provided in the third aspect, and the computer program product provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0025] 1. By adopting a mechanism of generating virtual occupant nodes at the bottom of prefabricated components and replacing nodes based on spatial intersection operations, the spatial subordination benchmark of the upper components can be established in advance without placing the bottom solid components. This effectively solves the rigid constraint problem in the existing technology that requires the bottom solid components to generate the upper components, thereby realizing the flexible construction of the top-down suspended prefabricated building construction model.

[0026] 2. By employing the computational logic of extracting the set of bottom vertices to generate a two-dimensional bounding rectangle and combining it with the extended depth to construct a three-dimensional bounding box, the effective bearing space range under the prefabricated component is defined. This effectively solves the problem of low accuracy in subsequent node matching caused by fuzzy calculation of the component's occupancy area in the existing technology, thereby realizing the accurate representation of virtual occupancy nodes in three-dimensional space and the writing of graph structures.

[0027] 3. By adopting a scheduling algorithm that calculates the topology depth based on the longest path hop count and merges parallel construction batches by depth, the complex spatial support tree is transformed into a time series that can be executed in parallel. This effectively solves the problem that the component installation sequence cannot adapt to spatial dependencies in the existing technology, thereby realizing the scientific arrangement of the construction time axis and the optimization of the parallel construction period. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of a scenario for the construction model building method of prefabricated buildings in this application embodiment;

[0029] Figure 2 This is a flowchart illustrating a method for constructing a prefabricated building construction model in an embodiment of this application.

[0030] Figure 3 This is another flowchart illustrating the prefabricated building construction model construction method in this application embodiment;

[0031] Figure 4 This is a schematic diagram of the physical device structure of a construction simulation system in the embodiments of this application. Detailed Implementation

[0032] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0033] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0034] Please see Figure 1This is a schematic diagram illustrating a scenario of the prefabricated building construction model construction method in this application embodiment. In large-scale prefabricated building projects, such as reverse construction or modular assembly projects, there is a need to compress the overall construction cycle, requiring multiple teams of technicians to conduct model construction work in parallel. Traditional underlying data engines have rigid dependency limitations, causing the 3D modeling instructions responsible for the superstructure to wait until the bottom foundation components are instantiated before they can be executed.

[0035] To resolve this data dependency conflict, Figure 1 The document demonstrates the processing logic of three core stages: initial placement from top to bottom, spatial intersection and node replacement, and gravity direction support detection.

[0036] In the first stage, for the input end responsible for top-down operations, the construction simulation system receives the placement instruction for the first precast component, generates the first precast component node in the three-dimensional virtual space, and generates the first virtual occupant node at its bottom boundary coordinates. This first virtual occupant node serves as an abstract data object of the lower-level assembly space, pre-establishing the spatial subordination benchmark of the upper-level components before the lower-level physical components are placed.

[0037] In the second stage, when the underlying component data is submitted, the system receives the placement instruction for the second prefabricated component. It then performs a spatial intersection operation between the spatial coordinate region corresponding to this instruction and the first virtual placeholder node to obtain a matching component node. Subsequently, the first virtual placeholder node is replaced with the matching component node, and a second virtual placeholder node is generated at the new bottom boundary. This process effectively eliminates the rigid constraint that upper-level components must rely on underlying physical components, allowing independent work data from top to bottom and bottom to top to be seamlessly integrated in three-dimensional virtual space.

[0038] In the third stage, to verify the structural stability after parallel operation assembly, the system generates geometrically intersecting test segments along the gravity direction axis based on the component nodes in the updated directed acyclic graph. It then extracts lower-level component nodes whose coordinates coincide with these geometrically intersecting test segments, forming pairs of adjacent component nodes with spatial support relationships. For example, when simulating the connection between the assembled cantilevered balcony slab and the load-bearing wall below, the system accurately captures the physical support state of both through geometrically intersecting test segments, eliminating side nodes without actual support relationships. Finally, the system extracts the time series parameters from the construction sequence timeline and writes them into the corresponding component nodes to obtain the prefabricated building construction model. This scenario logic not only meets the pre-construction requirements of multi-terminal parallel modeling but also ensures the physical rationality of the spatial support tree construction.

[0039] The following describes the process of the method provided in this implementation. Please refer to [link / reference]. Figure 2 This is a flowchart illustrating a method for constructing a prefabricated building construction model in an embodiment of this application.

[0040] S201. Receive the first prefabricated component placement instruction and generate the first prefabricated component node corresponding to the first prefabricated component placement instruction in the three-dimensional virtual space.

[0041] The first prefabricated component placement instruction refers to a data packet triggered by an input device, containing a specific component type and target 3D coordinates. The first prefabricated component node refers to the initial 3D model data object instantiated in memory by the system, corresponding to this instruction.

[0042] Specifically, when a user initiates the top-down reverse modeling process, the construction simulation system parses the input first precast component placement instruction, extracting the component identification code and target coordinate system matrix. Based on the component identification code, the system retrieves the corresponding 3D mesh data from a pre-set component database, applies the target coordinate system matrix for spatial transformation, and renders and generates the first precast component node in 3D virtual space.

[0043] In some embodiments, the generation of the first prefabricated component node can be achieved in several ways: Optionally, the construction simulation system parses the parameters in the instruction, calls the graphics application programming interface to draw the basic geometry at specified coordinates, and assigns the corresponding material texture to complete the node generation; Optionally, the construction simulation system reads the pre-compiled parametric component script, substitutes the size variables in the instruction for real-time geometric calculations, and outputs polygon mesh data to generate the node. It is understood that other methods can also be used to instantiate the node, which are not limited here. In some embodiments, there may be cases where the coordinates contained in the instruction exceed the virtual space boundary. In this case, the construction simulation system will extract the instruction coordinates for boundary verification. If the coordinates exceed a preset three-dimensional coordinate threshold range, the coordinate parameters will be clamped to the boundary extreme value before executing the node generation logic.

[0044] S202. Generate a first virtual occupant node at the bottom boundary coordinates of the first prefabricated component node to obtain an initial directed acyclic graph containing the first prefabricated component node and the first virtual occupant node.

[0045] Here, the bottom boundary coordinates refer to the lowest horizontal spatial range of the first prefabricated component node in the direction of gravity. The first virtual occupant node refers to an abstract data object generated based on these bottom boundary coordinates, used to represent the lower-level assembly space. The initial directed acyclic graph refers to a data structure that records the dependencies between the first prefabricated component node and the first virtual occupant node.

[0046] Specifically, after generating the first precast component node, the construction simulation system traverses the vertex data of that node, calculates the plane containing the minimum value in the Z-axis direction, and determines the bottom boundary coordinates. Then, using these boundary coordinates as a reference, the system extends downwards by a preset tolerance distance to construct an invisible bounding box as the first virtual placeholder node. The system creates a graph structure in memory, setting the first precast component node as the parent node and the first virtual placeholder node as the child node, establishing directed edges, and forming an initial directed acyclic graph.

[0047] In some embodiments, the generation of virtual placeholder nodes can be achieved in several ways: Optionally, the construction simulation system extracts the bottom surface contour line, extrudes it along the normal direction to generate a three-dimensional voxel, and marks the voxel as a placeholder attribute and writes it into the graph structure; Optionally, the construction simulation system calculates the coordinates of the bottom surface centroid and generates a spherical collision body with a default volume as the placeholder node, using the centroid as the origin. It is understood that other methods can also be used to implement the placeholder logic, which are not limited here. In some embodiments, there may be cases where the plane containing the bottom boundary coordinates is uneven. In this regard, the construction simulation system extracts the average Z-axis coordinates of all bottom vertices to construct a virtual fitting plane, and generates the first virtual placeholder node based on this fitting plane.

[0048] S203. Receive the second prefabricated component placement instruction, and perform a spatial intersection operation on the spatial coordinate region corresponding to the second prefabricated component placement instruction and the first virtual occupant node in the initial directed acyclic graph to obtain the matching component node.

[0049] The second prefabricated component placement instruction refers to the control data used to place the lower-level supporting components. The spatial coordinate region refers to the volume range occupied by the new component indicated by the instruction in three-dimensional space. The matching component node refers to the new component data object that, after intersection verification, is confirmed to be able to form a valid connection with the first virtual placeholder node.

[0050] Specifically, when the system receives a placement instruction for the second prefabricated component, it first calculates the spatial coordinate region of the component expected to be generated by the instruction. Then, the system calls the collision detection engine to perform a Boolean intersection operation between this spatial coordinate region and the first virtual placeholder node in the initial directed acyclic graph. If the volume of the intersection space generated by the operation is greater than a set threshold, the spatial matching is considered successful, and the component corresponding to the instruction is confirmed as a matched component node.

[0051] In some embodiments, spatial intersection operations can be implemented in multiple ways: Optionally, the construction simulation system converts the spatial coordinate region and the occupant node into a discrete voxel mesh, and counts the number of overlapping voxels to determine the intersection; alternatively, the construction simulation system extracts the axial bounding boxes of both and executes the separating axis theorem algorithm to test whether the bounding boxes overlap. It is understood that other methods can also be used to implement the intersection test, and this is not limited here. In some embodiments, there may be cases where the intersection operation result is a slight edge contact leading to a false judgment. To address this, the construction simulation system sets a minimum intersection depth threshold, and only outputs matching component nodes when the penetration depth of the intersection space is greater than this threshold.

[0052] S204. Replace the first virtual placeholder node in the initial directed acyclic graph with a matching component node, and generate a second virtual placeholder node at the bottom boundary coordinates of the matching component node to obtain the updated directed acyclic graph.

[0053] The replacement operation refers to changing the memory pointer of a node in the graph data structure. A second virtual placeholder node is a new abstract space object reserved for continuing downwards to match the component node. An updated directed acyclic graph (DAG) is a graph structure that reflects the latest component assembly state.

[0054] Specifically, after confirming the matching component node, the construction simulation system modifies the directed edge pointers in the initial directed acyclic graph, redirecting the edges that originally pointed to the first virtual placeholder node to the matching component node, and then destroys the first virtual placeholder node from memory. Next, the system extracts the bottom boundary coordinates of the matching component node, generates a second virtual placeholder node using the same logic as generating the first virtual placeholder node, and integrates it into the graph structure as a child node of the matching component node, thus completing the update of the directed acyclic graph.

[0055] In some embodiments, node replacement can be implemented in several ways: Optionally, the construction simulation system performs a memory overwrite operation, directly writing the data of the matching component node to the memory address where the first virtual placeholder node is located, and updating the node type identifier; alternatively, the construction simulation system creates a new matching component node in the graph, copies the incoming edge relationships of the original placeholder node to the new node, and then executes a node deletion command to remove the original placeholder node. It is understood that other methods can also be used to update the graph structure, and these are not limited here. In some embodiments, there may be cases where the bottom of the matching component node coincides with the virtual ground. In this case, the construction simulation system will detect the Z-value of the bottom boundary coordinates. If the Z-value is less than or equal to the ground elevation, the step of generating a second virtual placeholder node is skipped, and the updated directed acyclic graph is directly output.

[0056] S205. Based on the component nodes in the updated directed acyclic graph, generate geometrically intersecting test segments along the gravity direction axis, extract the lower-level component nodes that coincide with the coordinates of the geometrically intersecting test segments, and obtain adjacent component node pairs with spatial connection relationships.

[0057] Here, the gravity direction axis refers to a spatial vector perpendicular to the horizontal plane and pointing downwards. Geometric intersection test segments refer to rays or line segments used to detect spatial physical occlusion relationships. Adjacent component node pairs refer to two component nodes that have a direct vertical support relationship in physical space.

[0058] Specifically, the construction simulation system traverses all solid component nodes in the updated directed acyclic graph, using the bottom surface of each node as the emission source, and projects geometrically intersecting test segments downwards along the gravity direction axis. The system calculates the coordinates of the intersection points of these segments with the top surfaces of other component nodes in space. If a valid intersection point exists, the node closest to the emission source that is hit is extracted as the lower-level component node, and the emission node is bound to this lower-level component node to form a pair of adjacent component nodes with a spatial connection.

[0059] In some embodiments, intersection testing can be implemented in several ways: Optionally, the construction simulation system calls a ray tracing algorithm to calculate the intersection points of the ray with all polygonal faces in the scene, and extracts the nearest nodes by sorting them by distance; Optionally, the construction simulation system projects the component onto a two-dimensional plane, compares the Z-axis elevation differences in the overlapping area, and extracts the node with the smallest positive elevation difference as the lower-level node. It is understood that other methods can also be used to extract the connection relationship, and this is not limited here. In some embodiments, there may be cases where geometric intersection test segments pass through pre-reserved holes in the component, resulting in the lower-level node not being hit. To address this, the construction simulation system generates multiple test segments distributed in a grid on the bottom surface of the component, and determines the lower-level component nodes by combining the hit results of multiple segments.

[0060] S206. Construct a hierarchical mapping relationship between adjacent component node pairs to obtain a spatial support tree, and perform a topological sorting algorithm on the spatial support tree to extract the component node sequence and obtain the construction sequence time axis.

[0061] Among them, the hierarchical mapping relationship refers to the key-value pairs that record the supporting and supported logic between nodes. The spatial support tree refers to a tree structure with the basic components as the root node and the upper-level components as child nodes. The construction sequence timeline refers to the sequence of component installations arranged chronologically.

[0062] Specifically, the construction simulation system transforms the extracted pairs of adjacent component nodes into parent-child node relationships, with lower-level component nodes serving as parent nodes and upper-level component nodes as child nodes, thus generating a spatial support tree. Subsequently, the system executes topological sorting algorithms such as the Kahn algorithm or depth-first search on this spatial support tree to parse the dependency levels between nodes, prioritizing the extraction of nodes without prerequisite dependencies, sequentially generating a sequence of component nodes, and mapping them to the time dimension to generate a construction sequence timeline.

[0063] In some embodiments, topological sorting can be implemented in several ways: Optionally, the construction simulation system counts the in-degree of each node, iteratively extracts nodes with an in-degree of zero and adds them to the sequence, while simultaneously reducing the in-degree of their child nodes, until the entire tree has been traversed; alternatively, the construction simulation system executes a post-order traversal algorithm, records the exit timestamp of each node, and arranges the component node sequence in reverse order of the timestamps. It is understood that other methods can also be used to extract the sequence, and this is not limited here. In some embodiments, local circular dependencies may occur in the spatial support tree, causing topological sorting to fail. To address this, the construction simulation system executes a strongly connected component detection algorithm to identify and break non-load-bearing connection edges in the circular dependencies, and then re-executes the topological sorting algorithm.

[0064] S207. Extract the time series parameters from the construction sequence time axis, write the time series parameters into the corresponding component nodes in the updated directed acyclic graph, and obtain the prefabricated building construction model.

[0065] Among them, time series parameters refer to numerical values ​​or timestamps that characterize the order in which components are installed. Prefabricated building construction models are four-dimensional building information models that integrate geometric information, spatial relationships, and the time dimension.

[0066] Specifically, the construction simulation system parses the construction sequence timeline and extracts the time series parameters corresponding to each component node. The system traverses and updates the directed acyclic graph, locates the memory address of the specific component node, and writes the extracted time series parameters as new attribute fields into the node's data structure. After writing all parameters, the system outputs a prefabricated building construction model containing complete spatiotemporal information for subsequent four-dimensional construction animation simulations.

[0067] In some embodiments, parameter writing can be implemented in multiple ways: Optionally, the construction simulation system can batch modify the timestamp field in the component node table using database update statements; alternatively, the construction simulation system can use serialization technology to package and encode the time series parameters and component node data into a specific BIM file format for output. It is understood that other methods can also be used to generate the model, and this is not limited here. In some embodiments, there may be incompatibility between the time series parameter format and the external rendering engine. To address this, the construction simulation system will call a format conversion interface to map the internal time series parameters to a standard international time standard format (ISO 8601) string before performing the writing operation.

[0068] To address the issue of low accuracy in subsequent node matching caused by fuzzy calculations of component placement areas, the method provided in this implementation is described in more detail below. Please refer to [link / reference]. Figure 3 This is another flowchart illustrating the prefabricated building construction model construction method in this application embodiment.

[0069] S301. Receive the first prefabricated component placement instruction and generate a first prefabricated component node corresponding to the first prefabricated component placement instruction in the three-dimensional virtual space.

[0070] Refer to step S201, which will not be repeated here.

[0071] After generating the first prefabricated component node, the system needs to analyze its geometric features in order to accurately define the effective support space below it.

[0072] S302. Extract the three-dimensional mesh model of the first prefabricated component node and obtain the set of bottom vertices with the smallest Z-axis coordinate value in the three-dimensional mesh model.

[0073] In this context, a 3D mesh model refers to the geometric representation of a component's surface, consisting of vertices, edges, and faces. The bottom vertex set refers to the group of coordinate points located at the bottom of the component, participating in its support and connection.

[0074] Specifically, the construction simulation system accesses the geometric data buffer of the first precast component node and reads the coordinates of all vertices in the 3D mesh model. The system traverses these vertices, compares their Z-axis components, selects vertices whose Z-axis coordinate values ​​are equal to the global minimum, and combines these vertices into a set of bottom face vertices for subsequent boundary calculations.

[0075] In some embodiments, vertex extraction can be achieved in several ways: Optionally, the construction simulation system executes a vertex sorting algorithm to sort vertices in ascending order of Z-value, and extracts all vertices within the first value and its tolerance range; alternatively, the construction simulation system calculates the bounding box bottom of the mesh model and extracts vertices intersecting the bottom surface through ray projection. It is understood that other methods can also be used to obtain the set, and this is not limited here. In some embodiments, there may be cases where the bottom surface of the component has chamfers, resulting in very few vertices with absolute minimum values. To address this, the construction simulation system sets a Z-axis tolerance range and includes all vertices falling within this range into the bottom surface vertex set.

[0076] After obtaining the set of bottom vertices, the system needs to eliminate interference from irregular edges and extract the most compact 2D boundary. That is:

[0077] S303. Generate a two-dimensional bounding rectangle based on the extreme coordinates of the bottom vertex set to obtain the bottom boundary coordinates.

[0078] Here, extreme coordinates refer to the maximum and minimum values ​​of the vertex set along the X and Y axes. A two-dimensional bounding rectangle is the smallest rectangle that completely encloses the vertex set on the horizontal projection plane.

[0079] Specifically, the construction simulation system extracts the X-axis and Y-axis coordinates of all points in the bottom vertex set, and calculates the maximum, minimum, maximum, and minimum values ​​of the X-axis, Y-axis, and Y-axis, respectively. Using these four extreme coordinates as vertices, the system constructs an orthogonal two-dimensional enclosing rectangle on the two-dimensional plane, and extracts the corner coordinates of this rectangle as the bottom boundary coordinates.

[0080] In some embodiments, rectangle generation can be achieved in multiple ways: optionally, the construction simulation system directly generates an axial bounding box (AABB) by splicing extreme coordinates; optionally, the construction simulation system uses a rotating caliper algorithm to calculate the minimum area bounding rectangle (OBB) of the vertex set. It is understood that other methods can also be used for boundary calculation, and this is not limited here. In some embodiments, there may be cases where the component placement angle is tilted, resulting in an excessively large axial bounding box. To address this, the construction simulation system first performs principal component analysis (PCA) on the vertex set to obtain the principal direction, and then generates a two-dimensional bounding rectangle along the principal direction.

[0081] In some embodiments, to further optimize the compactness of the boundary coordinates, the construction simulation system executes a more accurate polygon fitting algorithm. Specifically, the system extracts the two-dimensional projected coordinates of the bottom vertex set, performs a convex hull algorithm on the two-dimensional projected coordinates to obtain a two-dimensional convex hull polygon; extracts each edge segment of the two-dimensional convex hull polygon, and generates corresponding bounding rectangles based on each edge segment as the reference direction, resulting in multiple sets of bounding rectangles; calculates the area of ​​each bounding rectangle in the multiple sets of bounding rectangles, extracts the target bounding rectangle with the smallest area value, and obtains a two-dimensional enclosing rectangle; finally, it extracts the corner coordinates of the two-dimensional enclosing rectangle to obtain the bottom boundary coordinates.

[0082] In this context, two-dimensional projective coordinates refer to the coordinate mapping of vertices on the XY plane. The convex hull algorithm refers to the computational process of finding the smallest convex polygon containing all points. The circumscribed rectangle is the rectangle that encloses the entire convex hull with one of its edges as its base.

[0083] Specifically, the construction simulation system projects the set of bottom vertices onto a two-dimensional plane and uses convex hull algorithms such as Graham's scan or divide-and-conquer to generate a two-dimensional convex hull polygon that encloses all projected points. The system iterates through each edge segment of the convex hull, calculating the bounding rectangle along that edge segment, forming multiple sets of bounding rectangles. Then, the system calculates the area of ​​each rectangle in the set, selects the target bounding rectangle with the smallest area, and extracts its corner coordinates as the final bottom boundary coordinates.

[0084] In some embodiments, convex hull calculation can be implemented in several ways: optionally, the construction simulation system uses the Jarvis stepwise algorithm to find the extrema one by one to construct the convex hull; optionally, the construction simulation system uses the QuickHull algorithm to recursively partition the point set to generate the convex hull. It is understood that other methods can also be used to generate polygons, and this is not limited here. In some embodiments, the large number of base vertices can lead to excessively long calculation times for traversing the circumscribed rectangle. To address this, the construction simulation system first performs mesh downsampling processing on the two-dimensional projected coordinates to remove redundant internal points before executing the convex hull algorithm.

[0085] After obtaining the bottom boundary coordinates, the system needs to expand them into a three-dimensional solid space for collision detection. That is:

[0086] S304. Combine the bottom boundary coordinates and the preset extension depth value to generate a three-dimensional bounding box, and obtain the first virtual placeholder node.

[0087] The preset extension depth value refers to the Z-axis offset configured by the system, representing the connection depth of typical components. The 3D bounding box refers to the cuboid space jointly defined by the bottom boundary coordinates and the extension depth.

[0088] Specifically, the construction simulation system reads the preset extension depth value from the system configuration file. Using a two-dimensional polygon formed by the bottom boundary coordinates as its top surface, the system extrudes downwards along the direction of gravity by a distance equal to the preset extension depth value, generating a closed three-dimensional bounding box. The system instantiates this three-dimensional bounding box as the first virtual placeholder node and assigns it spatial placeholder attributes.

[0089] In some embodiments, bounding box generation can be achieved in multiple ways: Optionally, the construction simulation system expands the two-dimensional boundary points into eight three-dimensional corner points through matrix transformation, and connects the corner points to generate voxels; alternatively, the construction simulation system calls the extrusion interface of the geometry engine, inputs the polygon contour and depth parameters, and directly outputs a three-dimensional solid. It is understood that other methods can also be used to construct nodes, and this is not limited here. In some embodiments, there may be cases where the preset extension depth value cannot adapt to components with special thicknesses. To address this, the construction simulation system dynamically matches and calls the corresponding adaptive extension depth value based on the structural type label of the first precast component node to generate a three-dimensional bounding box.

[0090] After completing the spatial construction of the virtual placeholder nodes, the system needs to integrate them into the overall data topology network. That is:

[0091] S305. Write the first prefabricated component node and the first virtual placeholder node into the memory graph structure to obtain the initial directed acyclic graph.

[0092] Refer to step S202, which will not be repeated here.

[0093] After establishing the initial dependencies, the system waits to receive assembly instructions from the lower-level components for spatial matching.

[0094] S306. Receive the second prefabricated component placement instruction, and perform a spatial intersection operation on the spatial coordinate region corresponding to the second prefabricated component placement instruction and the first virtual occupant node in the initial directed acyclic graph to obtain the matching component node.

[0095] Refer to step S203, which will not be repeated here.

[0096] However, it should be noted that when performing spatial intersection calculations on the spatial coordinate region corresponding to the placement command of the second precast component and the first virtual occupant node, in order to solve the problem of inconsistent matching accuracy for different types of components (such as steel structures and concrete structures) caused by using a fixed volume threshold, the construction simulation system will extract the connection node attribute tags of the second precast component (such as grouting sleeve connection, bolted rigid connection or flexible hinge connection), and match the corresponding dynamic volume calculation coefficient in the preset tolerance database according to the connection node attribute tags. Then, the theoretical volume value of the first virtual occupant node is multiplied by the dynamic volume calculation coefficient to obtain the dynamic intersection threshold. Only when the actual calculated intersection space volume is greater than the dynamic intersection threshold is the spatial matching determined to be successful and the matched component node is output. For example, when the system identifies a precast concrete column using "grouting sleeve connection", it will match a smaller dynamic volume calculation coefficient (such as 0.85) because the grouting material needs to occupy a certain space, thereby reducing the intersection threshold to allow for reasonable installation gaps. However, when it identifies a steel beam using "high-strength bolt end plate connection", the system will match a larger coefficient (such as 0.98), requiring an extremely high degree of spatial overlap to determine a successful match, thus greatly improving the engineering authenticity of prefabricated node matching.

[0097] Once the spatial matching is confirmed to be successful, the system needs to update the graph structure to reflect the actual component assembly status.

[0098] S307. Replace the first virtual placeholder node in the initial directed acyclic graph with a matching component node, and generate a second virtual placeholder node at the bottom boundary coordinates of the matching component node to obtain the updated directed acyclic graph.

[0099] Refer to step S204, which will not be repeated here.

[0100] To ensure that the component installation sequence conforms to the logic of physical gravity transmission, the system needs to extract the actual connection relationships between the components. That is:

[0101] S308. Based on the component nodes in the updated directed acyclic graph, generate geometrically intersecting test segments along the gravity direction axis, extract the lower-level component nodes whose coordinates coincide with the geometrically intersecting test segments, and obtain adjacent component node pairs with spatial connection relationships.

[0102] Refer to step S205, which will not be repeated here.

[0103] It should be noted that after obtaining multiple candidate component nodes through ray intersection testing, in order to avoid misjudging components that only have slight edge contact but cannot provide stable physical support as lower-level support nodes, the construction simulation system will extract the actual intersection coordinates of all rays and candidate component nodes, project these intersection coordinates onto a two-dimensional horizontal plane, and use the convex hull algorithm to generate an effective support polygon composed of these intersection points. Then, the three-dimensional centroid coordinates of the upper-level component node emitting the ray are calculated, and these centroid coordinates are also projected onto the two-dimensional horizontal plane to obtain the centroid projection point. The system will execute a judgment algorithm to determine if the point is inside the polygon. Only when the centroid projection point is strictly located inside the effective support polygon and the minimum distance from the edge of the polygon is greater than the preset safety eccentricity, will the corresponding candidate component node be confirmed as a lower-level component node that can provide stable support. For example, when simulating the assembly of a precast balcony slab with a huge cantilever structure, although its bottom may coincide with the Z-axis coordinate of a decorative slender column below (i.e., the ray hits the slender column), the system calculation found that the center of gravity projection point of the balcony slab fell outside the tiny support polygon provided by the slender column. This was determined to be an unstable support and was removed, thus effectively avoiding the error of stress imbalance of the suspended component during the simulated construction process.

[0104] In some embodiments, to simulate the physical support state between surfaces, the construction simulation system employs an array ray testing method. Specifically, the system extracts the bottom polygons of the component nodes in the updated directed acyclic graph, generates a two-dimensional sampling point array within these polygons, and generates a downward-extending ray along the gravity axis from each sampling point in the array, resulting in multiple geometrically intersecting test segments. It then extracts a set of candidate component nodes whose coordinates coincide with these geometrically intersecting test segments. From this set, it extracts the target node with the largest Z-axis coordinate value to obtain the lower-level component node. Finally, it combines the component node emitting the geometrically intersecting test segments with the lower-level component node to obtain adjacent component node pairs with spatial connection relationships.

[0105] Here, the two-dimensional sampling point array refers to the set of coordinate points distributed according to specific rules within the area of ​​the base polygon. The candidate component node set refers to all potential supporting components hit by the ray.

[0106] Specifically, the construction simulation system analyzes the polygonal geometric features of the bottom surface of the component nodes and generates a uniformly distributed array of two-dimensional sampling points within the polygons according to a preset grid spacing. Using each sampling point as the origin, the system emits rays along the negative Z-axis, forming multiple geometrically intersecting test line segments. The system records all component nodes penetrated by these rays in three-dimensional space, and after summarizing and deduplicating, obtains a set of candidate component nodes. Subsequently, the system compares the top Z-axis coordinate values ​​of each node in this set, extracts the node with the largest value as the lower-level component node that actually provides support, and pairs it with the emitting node to generate adjacent component node pairs.

[0107] In some embodiments, array generation can be achieved in several ways: Optionally, the construction simulation system generates an orthogonal mesh based on the bounding box of the base polygon, and removes mesh points outside the polygon to obtain sampling points; alternatively, the construction simulation system uses the Poisson disk sampling algorithm to generate uniformly distributed and non-overlapping sampling points within the base polygon. It is understood that other methods can also be used to achieve the distribution of sampling points, and this is not limited here. In some embodiments, there may be a situation where the area of ​​the base polygon is too small, resulting in an insufficient number of generated sampling points. To address this, the construction simulation system dynamically reduces the mesh spacing parameter, forcing the generation of at least three sampling points distributed in a triangle within the base polygon.

[0108] In some embodiments, to avoid misclassifying non-load-bearing components as support nodes, the construction simulation system introduces an attribute filtering mechanism. Specifically, the system acquires multiple initial collision nodes pierced by multiple geometrically intersecting test lines, extracts the structural attribute label for each initial collision node, and removes the corresponding initial collision node from the multiple initial collision nodes when the structural attribute label is a non-load-bearing label, thus obtaining a set of candidate component nodes.

[0109] In this context, the initial collision node refers to a component node that has not undergone attribute filtering and has geometrically intersected with the ray. Structural attribute labels are metadata identifying the stress characteristics of a component. Non-load-bearing labels indicate that a component does not possess structural support capabilities.

[0110] Specifically, after performing the ray intersection test, the construction simulation system collects all the initial collision nodes that have been penetrated. The system reads the in-memory database and extracts the structural attribute tags bound to each initial collision node. The system performs conditional judgments on the tag content; if non-load-bearing tags such as "ceiling" or "decorative panel" are identified, the node is deleted from the initial collision node list. After traversing and eliminating these tags, the system retains the nodes with load-bearing attributes and outputs the final set of candidate component nodes.

[0111] In some embodiments, attribute extraction can be achieved in multiple ways: optionally, the construction simulation system retrieves tags by querying the associated BIM attribute table using the node's unique identifier; alternatively, the construction simulation system directly parses the custom attribute dictionary in the node data structure to read the tag field. It is understood that other methods can also be used for attribute verification, which are not limited here. In some embodiments, some imported component nodes may lack structural attribute tags. In response, the construction simulation system will call the default rule engine and perform heuristic inference based on the component's volume and material parameters, temporarily assigning it a load-bearing or non-load-bearing tag.

[0112] When some imported component nodes lack structural attribute labels, the construction simulation system will call a pre-trained component load-bearing attribute prediction model to automatically infer and complete the labels. This component load-bearing attribute prediction model is essentially a deep learning classification model based on a fusion of Multilayer Perceptron (MLP) and Graph Neural Network (GNN), aiming to predict the stress properties of components by mining their geometric features and spatial topological relationships. During the model training phase, the system collects massive amounts of BIM component data from historically completed prefabricated building projects as training samples. The input data includes a set of scalar features of the components (such as the component's 3D bounding box aspect ratio, volume value, and material density parameters) and a set of topological features (such as the component's in-degree and out-degree values ​​in the historical spatial support tree). The output data is a binary probability value indicating whether the component is a load-bearing component (label 0 represents non-load-bearing, label 1 represents load-bearing). The specific training standard utilizes the Cross-Entropy Loss function to quantify the difference between the model's predicted probability distribution and the actual engineering label distribution. The Adam optimization algorithm iteratively updates the network weights during backpropagation until the classification accuracy on the validation set no longer improves for several consecutive cycles and the loss value converges to a preset minimum threshold, thus ensuring the model's generalization ability. During model usage, when the system detects that an initial collision node in the current directed acyclic graph lacks a structural attribute label, it automatically extracts the node's current volume, material density, bounding box ratio, and the number of connecting edges in the initial directed acyclic graph. These feature data are normalized and input into the component's load-bearing attribute prediction model. After forward propagation, the model outputs a confidence probability value between 0 and 1. When this probability value is greater than or equal to 0.5, the system determines that the node has load-bearing capacity and assigns it a "load-bearing label"; otherwise, it assigns a "non-load-bearing label." This significantly improves the engineering rigor and automation level of support relationship determination without manual intervention.

[0113] After extracting all adjacent component node pairs and constructing the spatial support tree, the system needs to convert it into an executable construction sequence. That is:

[0114] S309. Perform a topology sorting algorithm on the spatial support tree to obtain the longest path hop count from each component node in the spatial support tree to the root node, and obtain the topology depth value.

[0115] Among them, the longest path hop count refers to the maximum number of edges traversed from the current node along directed edges to the root node. The topology depth value is a quantitative indicator representing the hierarchical height of a component in the support system.

[0116] Specifically, the construction simulation system inputs the spatial support tree into the topology sorting engine. Starting from the root node representing the basic components, the engine traverses the tree structure layer by layer using a breadth-first search algorithm. During the traversal, the system records and updates the longest path hop count from each component node to the root node, assigning this hop count as the topology depth value to the corresponding component node.

[0117] In some embodiments, depth calculation can be implemented in several ways: Optionally, the construction simulation system initializes all node depths to zero and updates the depths of child nodes sequentially according to the topological sequence to the maximum value of the parent node's depth plus one; alternatively, the construction simulation system uses a recursive function to calculate and cache the depth of each node from top to bottom. It is understood that other methods can also be used to implement hierarchical quantization, which are not limited here. In some embodiments, there may be cases where the spatial support tree has multiple root nodes (i.e., multiple independent foundations). In this case, the construction simulation system creates a virtual super root node connecting all independent foundations and then performs the calculation of the longest path hop count.

[0118] After obtaining the topology depth value, the system needs to classify and merge components at the same construction level. That is:

[0119] S310. Merge component nodes with the same topology depth value into the same array set to obtain a component node sequence containing multiple parallel construction batch sets.

[0120] Here, an array set refers to a data structure in memory used to contiguously store pointers to nodes of the same type. A parallel construction batch set refers to a group of components that are physically independent of each other and can be assembled simultaneously.

[0121] Specifically, the construction simulation system traverses all component nodes and reads their topology depth values. The system initializes a series of array sets in memory, indexed by depth values, and pushes pointers of component nodes with the same topology depth value into the corresponding array sets. After classification, the system outputs a sequence of component nodes containing multiple sets of parallel construction batches, ordered by depth index.

[0122] In some embodiments, node merging can be implemented in several ways: Optionally, the construction simulation system uses a hash table data structure to quickly group nodes by depth value as the key and node list as the value; alternatively, the construction simulation system performs a quick sorting algorithm on all nodes according to their depth values, and extracts segments with consecutive identical values ​​as batch sets. It is understood that other methods can also be used to implement batch partitioning, which are not limited here. In some embodiments, there may be situations where the number of components in a certain parallel construction batch set exceeds the concurrency limit of hoisting equipment on the construction site. In response, the construction simulation system will perform a secondary partitioning of the batch set based on the equipment limit threshold, generating multiple sub-batch sets.

[0123] After batch partitioning, the system needs to allocate execution parameters with a time dimension to the sequences. That is:

[0124] S311. Assign incremental timestamp parameters to each set of parallel construction batches in the component node sequence in descending order of topology depth values ​​to obtain the construction sequence timeline.

[0125] The timestamp parameter refers to the time scale value used to drive the playback of the 4D construction animation.

[0126] Specifically, the construction simulation system extracts the component node sequence and traverses each set of parallel construction batches in descending order of topology depth (or ascending order, depending on the specific construction logic; here, it is assumed to be decreasing for the sake of the text). The system initializes a base timestamp and assigns this timestamp parameter to all components within the currently traversed batch set. Subsequently, it increments the timestamp according to the preset construction period step and continues to assign timestamps to the next batch set, ultimately generating a complete construction sequence timeline.

[0127] In some embodiments, time allocation can be implemented in multiple ways: Optionally, the construction simulation system reads the project schedule and maps batch sets to specific calendar dates to generate timestamps; alternatively, the construction simulation system uses relative time units (such as Day 1, Day 2) to sequentially accumulate timestamps. It is understood that other methods can also be used to generate the timeline, and this is not limited here. In some embodiments, there may be situations where the component volumes of different batch sets differ significantly, making the standard construction period step inapplicable. In response, the construction simulation system dynamically calculates and adjusts the incrementing timestamp step based on the total weight or volume of the components within each batch set.

[0128] In some embodiments, to prevent spatial interference between components within the same parallel batch during actual hoisting, the construction simulation system executes batch splitting logic. Specifically, the system extracts the 3D bounding boxes of all component nodes in the same parallel construction batch set, performs an intersection operation on the bounding boxes to obtain the interference volume value. When the interference volume value is greater than zero, the component nodes in the parallel construction batch set are abstracted as vertices in the interference topology graph, and the connections between component nodes with interference volume values ​​greater than zero are treated as undirected edges. A graph coloring algorithm is performed on the interference topology graph to calculate the minimum number of color types required, and component nodes assigned the same color are categorized into independent conflict-free sub-batch sets. Following the decreasing order of topology depth values, continuously increasing timestamp parameters are assigned to each conflict-free sub-batch set to obtain the construction sequence timeline.

[0129] The interference volume value refers to the volume of the overlapping area of ​​the three-dimensional bounding boxes of multiple components in three-dimensional space.

[0130] Specifically, the construction simulation system extracts the 3D bounding boxes of all component nodes within the same parallel construction batch set and performs spatial intersection operations on each pair. If the interference volume value of a pair of components is detected to be greater than zero, it indicates a risk of physical collision when they are hoisted at the same time. At this point, the system activates the topological conflict resolution mechanism. When constructing the interference topology graph, the system defines each potentially conflicting component node in the batch as a vertex. If the calculated interference volume value between two components is greater than zero, an undirected edge is established between these two corresponding vertices. Thus, the complex spatial collision relationships are reduced in dimensionality and transformed into a mathematically undirected graph structure.

[0131] Subsequently, the system executes a graph coloring algorithm on the interference topology graph. The core constraint of this algorithm is to ensure that no two vertices connected by any undirected edge are assigned the same color. Under this constraint, the system calculates the minimum number of color types (i.e., the number of colors). Since vertices assigned the same color are necessarily not connected by undirected edges, this means they absolutely do not interfere in three-dimensional space. Therefore, the system categorizes component nodes assigned the same color into an independent set of conflict-free sub-batches. Finally, the system assigns continuously increasing timestamp parameters to each set of conflict-free sub-batches according to the order of color assignment, thereby transforming spatial physical conflicts into staggered construction on the timeline.

[0132] For example, in the assembly simulation of the electromechanical pipeline integration module, the system detected intersecting ventilation duct A, fire water pipe B, and power cable tray C at the same elevation. After spatial intersection calculation, it was found that A interferes with B, B interferes with C, but A does not interfere with C. The system abstracts A, B, and C as three vertices and establishes undirected edges between AB and BC. After executing the graph coloring algorithm, the system assigns A as "red," and since B is connected to A, B cannot be red and is assigned as "blue." Since C is connected to B but not to A, C can reuse the "red" designation. Finally, the system assigns the "red" duct A and cable tray C to the first sub-batch (assigning the current timestamp), and the "blue" duct B to the second sub-batch (assigning an increasing timestamp). In this way, the system decouples the spatial conflicts of complex intersecting components without increasing the project duration, achieving optimal intelligent scheduling of parallel processes.

[0133] After generating the complete timeline, the system needs to embed the time information into the model data. That is:

[0134] S312. Extract the time series parameters from the construction sequence time axis, write the time series parameters into the corresponding component nodes in the updated directed acyclic graph, and obtain the prefabricated building construction model.

[0135] Refer to step S207, which will not be repeated here.

[0136] In this embodiment, by adopting a mechanism of generating virtual placeholder nodes at the bottom of prefabricated components and replacing nodes based on spatial intersection operations, and by combining a topological sorting algorithm to extract component node sequences, it is possible to pre-establish the spatial subordination benchmark of upper-level components and scientifically arrange the construction timeline when the bottom-level physical components are not placed. This effectively solves the problems in the prior art where rigid constraints must rely on the bottom-level physical components to generate upper-level components and the inability of the component installation sequence to adapt to spatial dependencies. Thus, it realizes the flexible construction of the top-down suspended prefabricated building construction model and the optimization of parallel construction periods.

[0137] The construction simulation system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference]. Figure 4 This is a schematic diagram of the physical device structure of a construction simulation system in this application embodiment.

[0138] It should be noted that, Figure 4 The structure of the construction simulation system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0139] like Figure 4As shown, the construction simulation system includes a CPU 401, which can perform various appropriate actions and processes according to a program stored in ROM 402 or a program loaded into RAM 403 from storage section 408, such as executing the methods described in the above embodiments. RAM 403 also stores various programs and data required for system operation. The CPU 401, ROM 402, and RAM 403 are interconnected via bus 404. I / O interface 405 is also connected to bus 404.

[0140] The following components are connected to I / O interface 405: input section 406 including audio input devices, push-button switches, etc.; output section 407 including liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 408 including hard disks, etc.; and communication section 409 including network interface cards such as LAN (Local Area Network) cards, modems, etc. Communication section 409 performs communication processing via a network such as the Internet. Drive 410 is also connected to I / O interface 405 as needed. Removable media 411, such as disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on drive 410 as needed so that computer programs read from them can be installed into storage section 408 as needed.

[0141] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by CPU 401, it performs the various functions defined in the present invention.

[0142] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0143] Specifically, the construction simulation system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements the prefabricated building construction model construction method provided in the above embodiment.

[0144] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the construction simulation system described in the above embodiments; or it may exist independently and not incorporated into the construction simulation system. The storage medium carries one or more computer programs, which, when executed by a processor of the construction simulation system, cause the construction simulation system to implement the prefabricated building construction model construction method provided in the above embodiments.

[0145] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0146] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

Claims

1. A method for constructing a prefabricated building construction model, characterized in that, The method, applied to a construction simulation system, includes: Upon receiving the first prefabricated component placement instruction, a first prefabricated component node corresponding to the first prefabricated component placement instruction is generated in a three-dimensional virtual space; A first virtual placeholder node is generated at the bottom boundary coordinates of the first precast component node, resulting in an initial directed acyclic graph containing the first precast component node and the first virtual placeholder node. Upon receiving the second prefabricated component placement instruction, a spatial intersection operation is performed on the spatial coordinate region corresponding to the second prefabricated component placement instruction and the first virtual occupant node in the initial directed acyclic graph to obtain a matching component node; The first virtual placeholder node in the initial directed acyclic graph is replaced with the matching component node, and a second virtual placeholder node is generated at the bottom boundary coordinates of the matching component node to obtain the updated directed acyclic graph. Based on the component nodes in the updated directed acyclic graph, a geometrically intersecting test line segment is generated along the gravity direction axis. The lower-level component nodes that coincide with the coordinates of the geometrically intersecting test line segment are extracted to obtain adjacent component node pairs with spatial connection relationships. A hierarchical mapping relationship is constructed between the adjacent component node pairs to obtain a spatial support tree. A topological sorting algorithm is then performed on the spatial support tree to extract the component node sequence, thereby obtaining the construction sequence timeline. Extract the time series parameters from the construction sequence time axis, and write the time series parameters into the corresponding component nodes in the updated directed acyclic graph to obtain the prefabricated building construction model.

2. The method according to claim 1, characterized in that, The step of generating a first virtual placeholder node at the bottom boundary coordinates of the first precast component node to obtain an initial directed acyclic graph containing the first precast component node and the first virtual placeholder node specifically includes: Extract the three-dimensional mesh model of the first prefabricated component node, and obtain the set of bottom vertices with the smallest Z-axis coordinate value in the three-dimensional mesh model; A two-dimensional enclosing rectangle is generated based on the extreme coordinates of the bottom vertex set, and the bottom boundary coordinates are obtained; A three-dimensional bounding box is generated by combining the bottom boundary coordinates and the preset extension depth value to obtain the first virtual placeholder node; Write the first prefabricated component node and the first virtual placeholder node into the memory graph structure to obtain the initial directed acyclic graph.

3. The method according to claim 2, characterized in that, The step of generating a two-dimensional enclosing rectangle based on the extreme coordinates of the bottom vertex set to obtain the bottom boundary coordinates specifically includes: Extract the two-dimensional projection coordinates of the set of bottom face vertices, and perform a convex hull algorithm on the two-dimensional projection coordinates to obtain a two-dimensional convex hull polygon; Extract each edge segment of the two-dimensional convex hull polygon, and generate a corresponding bounding rectangle with each edge segment as the reference direction to obtain a set of multiple bounding rectangles; Calculate the area value of each bounding rectangle in the set of multiple bounding rectangles, extract the target bounding rectangle with the smallest area value, and obtain the two-dimensional enclosing rectangle; Extract the corner coordinates of the two-dimensional enclosing rectangle to obtain the bottom boundary coordinates.

4. The method according to claim 1, characterized in that, The steps of generating geometrically intersecting test line segments along the gravity direction axis, extracting lower-level component nodes whose coordinates coincide with those of the geometrically intersecting test line segments, and obtaining pairs of adjacent component nodes with spatial connection relationships specifically include: Extract the bottom polygon of the component node in the updated directed acyclic graph, and generate a two-dimensional sampling point array inside the bottom polygon; Starting from each sampling point in the two-dimensional sampling point array, a ray extending downward along the gravity direction axis is generated to obtain multiple geometrically intersecting test line segments. Extract a set of candidate component nodes whose coordinates coincide with those of multiple geometrically intersecting test line segments; Extract the target node with the largest Z-axis coordinate value from the candidate component node set to obtain the lower-level component node; The component node that emits the geometrically intersecting test line segment is combined with the lower-level component node to obtain the adjacent component node pair with spatial connection relationship.

5. The method according to claim 4, characterized in that, The step of extracting the set of candidate component nodes that coincide with the coordinates of the multiple geometrically intersecting test line segments specifically includes: Obtain multiple initial collision nodes that are penetrated by multiple geometrically intersecting test line segments, and extract the structural attribute labels of each initial collision node; When the structural attribute label is a non-load-bearing label, the corresponding initial collision node is removed from the plurality of initial collision nodes to obtain the candidate component node set.

6. The method according to claim 1, characterized in that, The step of extracting the component node sequence by performing a topological sorting algorithm on the spatial support tree to obtain the construction sequence timeline specifically includes: A topology sorting algorithm is performed on the spatial support tree to obtain the longest path hop count from each component node in the spatial support tree to the root node, thereby obtaining the topology depth value; Component nodes with the same topology depth value are merged into the same array set to obtain the component node sequence containing multiple sets of parallel construction batches; In descending order of the topology depth value, an incremental timestamp parameter is assigned to each set of parallel construction batches in the component node sequence to obtain the construction sequence time axis.

7. The method according to claim 6, characterized in that, The step of assigning incremental timestamp parameters to each set of parallel construction batches in the component node sequence according to the decreasing order of the topology depth value to obtain the construction sequence time axis specifically includes: Extract the three-dimensional bounding boxes of all component nodes in the same set of parallel construction batches, and perform an intersection operation on the three-dimensional bounding boxes to obtain the interference volume value; When the interference volume value is greater than zero, the component nodes in the set of parallel construction batches are abstracted as vertices in the interference topology graph, and the connection between the component nodes with interference volume values ​​greater than zero is taken as undirected edges. The graph coloring algorithm is applied to the interference topology graph to calculate the minimum number of color types required, and the component nodes assigned the same color are classified into independent conflict-free sub-batch sets. The construction sequence timeline is obtained by assigning continuously increasing timestamp parameters to each set of conflict-free sub-batches in descending order of topology depth value.

8. A construction simulation system, characterized in that, The construction simulation system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the construction simulation system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is run on the construction simulation system, it causes the construction simulation system to perform the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the construction simulation system, the construction simulation system performs the method as described in any one of claims 1-7.

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