A BIM-based dynamic simulation method and system for construction schemes of complex building nodes

Abstract

This application relates to a BIM-based dynamic simulation method and system for construction schemes of complex building nodes, belonging to the field of information-based construction management technology for building engineering. The method includes: adaptively dividing the construction area of ​​the node BIM model based on multi-dimensional feature clustering, and defining heterogeneous base units based on the adaptive division results; dynamically dividing the construction scheme parameters based on the influence patterns according to the heterogeneous base units to obtain a bipartite construction parameter set; and performing a two-stage dynamic simulation of the construction scheme based on the bipartite construction parameter set, combining the heterogeneous base units and the node BIM model to obtain the node construction simulation results. This invention solves the problems in traditional complex node construction simulation, such as insufficient overall simulation accuracy due to the lack of effective deconstruction of complex nodes, reliance on fixed time quotas and inflexible simulation processes, difficulty in quickly assessing the impact of different schemes, and difficulties in scheme comparison and optimization.

Description

Technical Field

[0001] This application relates to the field of information-based construction management in building engineering, and in particular to a dynamic simulation method and system for construction schemes of complex building nodes based on BIM. Background Technology

[0002] As large-scale and complex construction projects continue to advance, the construction quality and efficiency of complex nodes directly affect the overall project progress and cost control. Accurate simulation of construction plans has gradually become a key technical requirement for ensuring project safety and improving construction efficiency.

[0003] Currently, traditional methods for simulating complex node construction do not effectively deconstruct the nodes and cannot achieve refined simulation of local differences in the nodes, resulting in insufficient overall simulation accuracy. At the same time, these methods mostly rely on fixed time quotas and lack flexibility in the simulation process, making it difficult to quickly assess the impact of different construction schemes. Ultimately, this makes it difficult to compare and optimize construction schemes, thus restricting the scientific and efficient nature of engineering decision-making. Summary of the Invention

[0004] This application provides a BIM-based dynamic simulation method and system for construction schemes of complex building nodes, which improves the current situation in traditional complex node construction simulation, which suffers from insufficient overall accuracy due to the lack of effective node deconstruction, reliance on fixed time quotas and inflexible simulation, making it difficult to quickly assess the impact of schemes and thus difficult to compare and optimize.

[0005] The embodiments of this application disclose the following technical solutions:

[0006] In a first aspect, embodiments of this application provide a dynamic simulation method for construction schemes of complex building nodes based on BIM, the method comprising:

[0007] The construction area of ​​the node BIM model is adaptively divided based on multidimensional feature clustering, and heterogeneous base units are defined based on the adaptive division results.

[0008] Based on the heterogeneous base unit, the construction scheme parameters are dynamically divided according to the influence mode to obtain a binary construction parameter set, wherein the binary construction parameter set includes a subset of baseline construction parameters and a subset of dynamic construction parameters.

[0009] Based on the binary construction parameter set, and combining the heterogeneous base unit and the node BIM model, a two-stage dynamic simulation of the construction scheme is performed to obtain the node construction simulation results.

[0010] Secondly, embodiments of this application provide a dynamic simulation system for construction schemes of complex building nodes based on BIM, the system comprising:

[0011] The area division and unit definition module is used to adaptively divide the construction area of ​​the node BIM model based on multidimensional feature clustering, and define heterogeneous base units based on the adaptive division results.

[0012] The construction parameter binary module is used to dynamically divide the construction scheme parameters based on the influence mode according to the heterogeneous base unit to obtain a binary construction parameter set, wherein the binary construction parameter set includes a subset of baseline construction parameters and a subset of dynamic construction parameters.

[0013] The two-stage dynamic simulation module is used to perform a two-stage dynamic simulation of the construction scheme based on the binary construction parameter set, combined with the heterogeneous base unit and the node BIM model, and to obtain the node construction simulation results.

[0014] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0015] This application proposes a BIM-based dynamic simulation method and system for construction schemes of complex building nodes. By processing the node BIM model step-by-step, dividing construction scheme parameters, constructing a node influence pattern library, and conducting a two-stage dynamic simulation, it achieves refined and accurate dynamic simulation of construction schemes for complex building nodes. First, the node BIM model of the target complex node is obtained. After analyzing and determining the common base level, meshing is performed. Multi-dimensional feature clustering is used to adaptively divide the construction area and define heterogeneous base units. Next, the simulation target indicators and construction scheme parameters are extracted. Through correlation analysis, a subset of baseline construction parameters and a subset of dynamic construction parameters are divided to form a bipartite construction parameter set. Then, prior sample data is collected based on the dynamic construction parameter subset, and a node influence pattern library is constructed through dimensional clipping and independent modeling. Finally, a two-stage dynamic simulation is conducted based on the bipartite construction parameter set and heterogeneous base units. First, the heterogeneous base BIM model is initialized using baseline parameters to obtain first-order baseline simulation results. Then, the node influence pattern library is called to calculate the dynamic influence coefficients and correct the baseline results, ultimately obtaining the node construction simulation results.

[0016] The technical solution of this application solves the problems of low simulation accuracy due to rough model processing, indiscriminate processing of construction parameters that cannot adapt to dynamic influencing factors, and lack of targeted basic data support in the simulation process in traditional construction simulation of complex building nodes. It avoids the situation where the simulation results are out of touch with the actual construction and key construction risks are not identified due to unreasonable parameter division or lack of dynamic correction, and improves the accuracy, flexibility and reliability of dynamic simulation of construction schemes for complex building nodes. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating the dynamic simulation method for construction schemes of complex building nodes based on BIM provided in this application embodiment;

[0019] Figure 2 A schematic diagram of the structure of the BIM-based dynamic simulation system for construction schemes of complex building nodes provided in this application embodiment.

[0020] The components represented by each number in the attached diagram are explained below:

[0021] Module 01 for area division and unit definition, Module 02 for construction parameter division, and Module 03 for two-stage dynamic simulation. Detailed Implementation

[0022] This application provides a BIM-based dynamic simulation method and system for construction schemes of complex building nodes, which solves the technical problems in the existing technology that traditional complex node construction simulation does not effectively deconstruct the nodes, resulting in insufficient overall accuracy, relies on fixed time quotas and is not flexible in simulation, and is difficult to quickly assess the impact of the scheme, thus making it difficult to compare and optimize.

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0025] In the description of this application, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0026] Example 1, as shown in the appendix Figure 1 As shown, this application provides a dynamic simulation method for construction schemes of complex building nodes based on BIM. The method includes the following steps:

[0027] S110: Adaptively divide the construction area of ​​the node BIM model based on multidimensional feature clustering, and define heterogeneous base units based on the adaptive division results;

[0028] In this embodiment of the application, in the scenario of large and complex construction projects involving the construction simulation of complex nodes, in order to achieve refined simulation of complex nodes, it is necessary to first divide the node BIM model into construction areas and define heterogeneous base units to improve the accuracy and efficiency of subsequent dynamic simulation of construction schemes.

[0029] Specifically, the first step is to obtain the BIM model of the target complex node and analyze it to determine the common base layer level. This process needs to be combined with the actual construction requirements to ensure that the common base layer level can accurately reflect the foundation composition and construction-related attributes of the node, laying the foundation for subsequent operations.

[0030] Furthermore, based on the established common base hierarchy, the node BIM model is meshed to form a mesh BIM model. Mesh generation must conform to the structural characteristics and construction feasibility of the nodes to ensure that the resulting mesh can effectively support subsequent feature extraction and cluster analysis.

[0031] Furthermore, after completing the grid division, the multi-dimensional feature vectors of the grid BIM models are obtained by traversing them, and then the unsupervised clustering algorithm is used to classify the multiple grid BIM models and divide them into multiple construction feature clusters.

[0032] Finally, multiple heterogeneous foundation units are defined based on the identified multiple construction feature clusters, and the inherent parameters of each heterogeneous foundation unit are marked to clarify the foundation construction attributes of different units.

[0033] This step, by clearly defining the heterogeneous base unit and its inherent parameters, provides a precise basic unit carrier for the subsequent parameter division of the construction scheme and the two-stage dynamic simulation, ensuring that the subsequent simulation process can be carried out based on a clear unit division and improving the fit between the simulation results and the actual construction.

[0034] Step S110 in the method provided in this application embodiment includes:

[0035] Obtain the node BIM model of the target complex node, and analyze and determine the common base level of the node BIM model;

[0036] Based on the common base hierarchy, the node BIM model is meshed to obtain a mesh BIM model;

[0037] The multidimensional feature vectors of the grid BIM models are obtained by traversal, and the multiple grid BIM models are divided into multiple construction feature clusters by combining an unsupervised clustering algorithm.

[0038] Multiple heterogeneous substrate elements are defined based on multiple construction feature clusters, and the inherent parameters of the heterogeneous substrate elements are marked.

[0039] In this embodiment of the application, in order to achieve a refined dynamic simulation of the construction scheme for complex building nodes, it is necessary to construct a basic simulation unit that fits the actual construction by performing layered processing and feature clustering of the node BIM model, so as to improve the accuracy and efficiency of subsequent construction scheme simulation and provide a reliable carrier for dynamic division of construction parameters and two-stage simulation.

[0040] Specifically, the first step is to obtain the node BIM model of the target complex node, and then analyze and determine the common base level of the node BIM model to ensure that the subsequent processing of the node BIM model can fit the actual construction operation logic and avoid the simulation from deviating from the actual construction scenario.

[0041] The method provided in this application embodiment, which involves obtaining the node BIM model of the target complex node and analyzing and determining the common base level of the node BIM model, includes:

[0042] The node BIM model is decomposed based on construction operability by combining the prior knowledge of the target complex nodes.

[0043] Based on the model decomposition results, the smallest construction unit that meets the standardized process constraints and can be repeatedly measured is extracted, and the corresponding common base level is defined.

[0044] The common base layer includes coupled material level information and process list information.

[0045] Specifically, the node BIM model is first decomposed based on construction operability by combining the prior knowledge of the target complex nodes. The prior knowledge of the nodes covers common structural forms of complex nodes, the conventional operation sequence in construction, and the process adaptation requirements of different parts. For example, for large-span steel structure nodes, the prior knowledge includes the splicing sequence of steel structure components, the applicable parts of welding processes, and the spatial constraints of hoisting operations.

[0046] During the decomposition process, based on the acquired prior knowledge, the node BIM model will be broken down into multiple sub-modules that correspond to the actual construction steps to avoid decomposition results that cannot correspond to construction operations. For example, steel structure areas that require continuous welding will not be split into multiple independent sub-modules to prevent the break in process logic during subsequent simulations.

[0047] Furthermore, after completing the model decomposition, the smallest construction unit that meets the standardized process constraints and can be repeatedly measured is extracted based on the model decomposition results.

[0048] Standardized process constraints refer to compliance with industry-standard construction processes, such as the standard thickness of each concrete pour and the standard spacing of reinforcing bars. Furthermore, repeatable measurement requires that the quantity of work for the construction unit can be calculated using a clearly defined measurement method, such as a curtain wall installation unit measured by area or a pipe laying unit measured by length.

[0049] Taking a complex electromechanical junction as an example, after decomposition, the smallest construction units such as single-section pipeline installation and single valve connection can be extracted. These smallest construction units not only meet the standardized process requirements of electromechanical installation, but can also be repeatedly measured through dimensions such as length and quantity, so that there will be no ambiguous units with non-standard processes or difficult measurement.

[0050] After extracting the smallest construction unit, a common base level is defined, which includes coupled material level information and process list information. The material level information covers the types, specifications, and quantities of materials required for the smallest construction unit. For example, the material level information for a single pipe section installation includes the pipe material, pipe diameter, and single section length.

[0051] In addition, the process list information includes the specific steps required to complete the construction unit and the order in which each step is performed. For example, the process list information for a single section of pipe installation includes steps such as pipe cutting, pipe end grinding, pipe connection, and pressure testing.

[0052] This step couples material hierarchy information with process list information into a common base level, so that in subsequent operations, as long as this level is associated, the correlation data between materials and processes can be obtained synchronously. This avoids the problem of materials and processes being disconnected during subsequent simulations and provides complete basic data support for subsequent steps such as mesh generation and parameter labeling.

[0053] Furthermore, after defining the common base level, the node BIM model is meshed based on the common base level to obtain the mesh BIM model.

[0054] Specifically, the density and range of the grid division must strictly match the size and distribution of the smallest construction unit in the common base level to ensure that each grid can accurately correspond to the core construction area of ​​the smallest construction unit. This will prevent a single grid from covering multiple significantly different construction units due to excessively large grid size, and will also prevent unnecessary computational load due to excessively small grid size.

[0055] For example, for complex nodes containing multiple standardized curtain wall installation units, the node BIM model is divided into equally sized grids according to the size of each curtain wall installation unit, so that each grid exactly covers the construction range of one curtain wall installation unit, ensuring that the subsequent feature extraction of the grid can be directly associated with the attributes of the specific construction unit.

[0056] Furthermore, after completing the grid division, the multi-dimensional feature vectors of the grid BIM model are obtained through traversal to fully capture the construction-related attributes of each grid, ensuring that the clustering results can accurately reflect the differences and commonalities of different grids at different feature levels.

[0057] In the method provided in this application embodiment, the multidimensional features include at least geometric features, spatial features, process features, and logical features.

[0058] Specifically, when extracting geometric features, data such as the size, shape, surface area, and volume of each grid are recorded. For example, if a grid corresponds to a cylindrical steel structure element, its geometric features will include the diameter, height, and lateral surface area of ​​the cylinder. Furthermore, when extracting spatial features, information such as the grid's three-dimensional coordinates in the node BIM model and its relative positional relationship with adjacent grids is collected. For instance, if a grid is located in the top region of a node, its spatial features will indicate the elevation of that region and its vertical distance from the bottom supporting structure grid.

[0059] Simultaneously, when extracting process features, the process requirements of the corresponding construction units in the common base layer are correlated, such as whether welding or high-precision assembly is required. Furthermore, when extracting logical features, the construction sequence of the corresponding construction unit in this grid with other grid construction units is clearly defined. For example, if pipe installation in a certain grid needs to be carried out after the support construction in an adjacent grid is completed, its logical features will record this sequence relationship. By comprehensively collecting features from the above four dimensions, a multi-dimensional feature vector that fully reflects the construction attributes of each grid is formed.

[0060] Furthermore, after obtaining the multidimensional feature vectors of all grids, an unsupervised clustering algorithm is used to divide the multiple grid BIM models into multiple construction feature clusters. Specifically, during the clustering process, the unsupervised clustering algorithm automatically identifies grids with similar feature vectors and groups them into the same construction feature cluster, ensuring that grids within the same cluster have a high degree of consistency in terms of construction requirements, operational difficulty, and resource allocation.

[0061] For example, meshes whose geometric features are all rectangular, whose spatial features are all located in the middle layer of nodes, whose process features are all bolted connections, and whose logical features all require construction after concrete pouring are grouped into the same construction feature cluster, so that subsequent processing of this cluster can be batch-adapted to similar construction parameters.

[0062] Finally, based on the identified multiple construction feature clusters, multiple heterogeneous base elements are defined, and the inherent parameters of the heterogeneous base elements are marked to clarify the foundation construction attributes of each element, ensuring that the simulation process can fit the construction characteristics of different elements and improve the matching degree between simulation results and actual construction.

[0063] In the method provided in this application embodiment, the inherent parameters of the unit include at least the reference working hours, reference manual labor configuration, reference mechanical configuration, and reference material consumption.

[0064] Specifically, when defining heterogeneous base units, construction feature clusters are used as units to integrate the common construction attributes of meshes within the same cluster into the core attributes of heterogeneous base units, so that each heterogeneous base unit can represent a set of meshes with similar construction features.

[0065] Furthermore, when marking the inherent parameters of the unit, the material and process information of the common base layer and the industry construction quota standards will be combined to determine the specific parameter values ​​for each heterogeneous base unit.

[0066] For example, a heterogeneous base unit corresponds to a steel structure mesh cluster for batch welding construction. Its unit inherent parameters will mark the baseline man-hours required to complete the construction of all meshes in the cluster, the baseline man-hour configuration of 3 certified welders, the baseline machine configuration of 1 welding robot, and the baseline material consumption of steel of the corresponding specification. By clarifying these parameters, accurate basic data support is provided for the dynamic simulation of subsequent construction plans.

[0067] S120: Based on the heterogeneous base unit, the construction scheme parameters are dynamically divided according to the influence mode to obtain a binary construction parameter set, wherein the binary construction parameter set includes a subset of baseline construction parameters and a subset of dynamic construction parameters.

[0068] In this embodiment of the application, in order to distinguish the parameter types in the construction scheme parameters that have different degrees of influence on the simulated target indicators, it is necessary to divide the construction scheme parameters based on the influence mode to form two types of parameter subsets: baseline and dynamic, so as to provide targeted parameter basis for the subsequent two-stage dynamic simulation.

[0069] Specifically, the simulation target indicators of the target complex nodes are first obtained, and the construction plan information is analyzed to extract the construction plan parameters. Among them, the simulation target indicators need to be determined based on the needs of construction simulation, and should cover at least one of the following categories: quantity indicators and cost indicators. The former is used to reflect the scale of the completed construction work, and the latter is used to reflect the cost consumption during the construction process.

[0070] In addition, the construction plan parameters are extracted from existing construction plan documents, including various parameter information related to the construction process. These parameters together constitute the basic data for subsequent division.

[0071] Furthermore, the extracted construction scheme parameters and simulated target indicators are randomly combined to obtain multiple correlation analysis groups. Each correlation analysis group consists of a single construction scheme parameter and a single simulated target indicator. Through comprehensive random combination, it is ensured that the correlation between all construction scheme parameters and each simulated target indicator can be included in the analysis scope.

[0072] Furthermore, correlation analysis is performed on the acquired multiple correlation analysis groups to determine the degree of correlation between the construction scheme parameters and the simulated target indicators. During the correlation analysis process, the correlation strength value between each group of parameters and indicators is calculated using data, and then this correlation strength value is compared with the preset significance constraint standard.

[0073] When the correlation strength value meets the significance constraint, it indicates that the corresponding construction scheme parameter has a significant impact on the simulated target index, and such parameters will be identified as members of the dynamic construction parameter subset. Conversely, if the correlation strength value does not meet the significance constraint, it indicates that the construction scheme parameter has a small impact on the simulated target index and can be used as a component of the baseline construction parameter subset.

[0074] Finally, by combining the determined subset of dynamic construction parameters with all the initially extracted construction scheme parameters, a reverse selection is performed to determine the subset of baseline construction parameters.

[0075] Through the above steps, a binary set of construction parameters is formed, corresponding to parameters with significant and minor influences respectively. This allows for focused adjustments to the dynamic construction parameter subset during subsequent simulations, while maintaining relative stability of the baseline construction parameter subset. This ensures the accuracy of the simulation while avoiding unnecessary computational redundancy.

[0076] Step S120 in the method provided in this application embodiment includes:

[0077] Obtain the simulated target indicators of the target complex node, and parse the construction plan information to extract the construction plan parameters, wherein the simulated target indicators include at least one of the following: engineering quantity indicators and engineering cost indicators.

[0078] The parameters of the construction plan are traversed and randomly combined with the simulated target indicators to obtain multiple correlation analysis groups;

[0079] Correlation analysis is performed on multiple association analysis groups to determine the construction scheme parameters of multiple association analysis groups whose correlation analysis results satisfy the preset significance constraints as the subset of dynamic construction parameters;

[0080] The baseline construction parameter subset is determined by combining the dynamic construction parameter subset with the construction scheme parameters.

[0081] In this embodiment of the application, in order to accurately distinguish the degree of influence of construction scheme parameters on the simulation results of complex node construction, and to avoid the simulation being unable to respond to changes in key variables due to all parameters being processed in a fixed mode, it is necessary to divide the parameter subsets through correlation analysis and inverse selection to form two types of construction parameter sets: baseline and dynamic. This provides targeted parameter basis for the subsequent two-stage dynamic simulation and improves the fit between the simulation results and actual construction.

[0082] First, we obtain the simulated target indicators for the complex nodes and analyze the construction plan information to extract the construction plan parameters, so as to clarify the core measurement standards and key influencing factors of the construction simulation and provide basic data support for the subsequent correlation analysis of parameters and indicators.

[0083] Specifically, the simulation targets must be determined around the core objectives of the construction simulation, including at least one of the following: quantity-based indicators and cost-based indicators. Quantity-based indicators measure the scale of completed work, such as the welding length or number of bolts installed at a steel structure node. Cost-based indicators are used to calculate resource consumption during construction, such as labor costs and material procurement costs for a curtain wall node.

[0084] When extracting parameters for the construction plan, it is necessary to sort out all parameters related to the construction process from materials such as construction organization design and technical disclosure documents, covering multiple dimensions such as spatial location, physical properties, environmental logic, and construction organization, to ensure that no key parameters are omitted in subsequent analysis.

[0085] Spatial location includes at least the installation elevation and horizontal coordinates, such as the hoisting height of large-span steel structure nodes and the horizontal and vertical positioning of curtain wall units on the building facade. In addition, physical properties include at least the component weight, dimensions, and geometric curvature, such as the diameter and wall thickness of electromechanical pipes and the bending radius of curved steel structure components.

[0086] Meanwhile, environmental logic includes at least weather influencing factors and transportation route complexity, such as the rainfall intensity coefficient during rainy season construction and the degree of congestion on the transportation route from the processing yard to the work site. In addition, construction organization includes at least the skill level of the work teams and the handover status of the work site, such as the number and skill level of certified personnel in the welding team and the cleanup and acceptance status of the work site after the completion of the previous process.

[0087] Furthermore, after obtaining the simulated target indicators and construction plan parameters, the construction plan parameters and simulated target indicators are randomly combined to obtain multiple correlation analysis groups. Each correlation analysis group contains only one construction plan parameter and one simulated target indicator, such as combinations like installation elevation (parameter) - welding workload (indicator), or team skill level (parameter) - labor cost (indicator).

[0088] By comprehensively traversing the combinations, we can ensure that each construction scheme parameter can be associated with each type of simulated target indicator, thereby avoiding the situation where the impact of a certain type of parameter on the indicator is not included in the analysis due to incomplete combinations, and laying the foundation for the comprehensiveness of subsequent related analyses.

[0089] Furthermore, after completing the construction of the correlation analysis groups, correlation analysis is performed on multiple correlation analysis groups to determine the correlation strength between the construction scheme parameters and the simulated target indicators.

[0090] Specifically, in the relevant analysis process, the correlation coefficient between each set of parameters and indicators will be calculated through data, and then the correlation coefficient will be compared with the preset significance constraint standard to distinguish the construction scheme parameters that have a significant impact on the simulated target indicators and those that have a weak impact.

[0091] If the correlation coefficient meets the significance constraint, it indicates that the construction scheme parameter has a significant impact on the simulated target index, and it is classified into the dynamic construction parameter subset. For example, the installation elevation in the spatial location parameter significantly affects the hoisting workload and machinery usage cost, and is therefore classified as a dynamic construction parameter. Conversely, if the correlation coefficient does not meet the significance constraint, it indicates that the parameter has a weak impact on the index and is not included in the dynamic parameter category for the time being.

[0092] Finally, a baseline construction parameter subset is determined by combining the dynamic construction parameter subset with all construction scheme parameters. Specifically, the inverse selection process involves removing parameters already included in the dynamic construction parameter subset from all construction scheme parameters, leaving the baseline construction parameter subset. These parameters typically have a stable and weak impact on the simulated target indicators. For example, the standard installation time for a certain specification bolt varies minimally under different construction scenarios, and therefore is classified as a baseline construction parameter.

[0093] By dividing the process into the above steps, a binary set of construction parameters with clearly defined functions can be formed. In subsequent simulations, dynamic parameters can be adjusted in a focused manner while keeping the baseline parameters stable. This ensures the flexibility of the simulation and avoids unnecessary computational redundancy.

[0094] S130: Based on the binary construction parameter set, and combining the heterogeneous base unit and the node BIM model, perform a two-stage dynamic simulation of the construction scheme to obtain the node construction simulation results.

[0095] In this embodiment of the application, in order to balance the stability and flexibility of the simulation and avoid the difference in the impact of different parameters on the results due to the inability of a single simulation mode to adapt to the results, the simulation needs to be carried out step by step in two stages: benchmark simulation and dynamic simulation. The benchmark simulation lays the foundation, the dynamic simulation corrects and optimizes the accuracy, and finally obtains the node construction simulation results that fit the actual construction situation.

[0096] Specifically, firstly, a subset of baseline construction parameters is extracted based on the bipartite construction parameter set. Then, the node BIM model is randomly cropped according to the heterogeneous base unit to obtain the heterogeneous base BIM model. This step must ensure that the cropped heterogeneous base BIM model can completely correspond to the previously defined heterogeneous base unit. At the same time, the extraction of the baseline construction parameter subset must accurately match the foundation construction requirements of each heterogeneous base unit, providing accurate data and model support for subsequent initialization simulation.

[0097] Furthermore, based on a subset of baseline construction parameters, multiple heterogeneous foundation BIM models are traversed and initialized, and construction simulations are performed to obtain first-order baseline simulation results. The initialization process requires matching the parameter values ​​in the subset of baseline construction parameters to the corresponding heterogeneous foundation BIM models one by one. The simulation process strictly follows the construction logic set by the baseline parameters to ensure that the first-order baseline simulation results can reflect the foundation execution of the construction plan under stable parameter conditions.

[0098] Furthermore, after completing the first-order baseline simulation, pattern matching is performed in the nodal influence pattern library based on a subset of dynamic construction parameters to obtain multiple dynamic influence patterns. Subsequently, the true values ​​of the subset of dynamic construction parameters are input into multiple dynamic influence patterns to obtain multiple sets of simulation result influence coefficients.

[0099] After obtaining the influence coefficients of the simulation results, multiple sets of influence coefficients are output in a structured manner using the model coordinate features corresponding to the subset of dynamic construction parameters as indexes, and a positional mapping relationship is established with the node BIM model. Specifically, the indexes of the coordinate features must accurately correspond to the spatial location of the node BIM model, and the establishment of the positional mapping relationship must ensure that the influence coefficients are accurately associated with the specific model area in which they act, to avoid mismatches between coefficients and locations.

[0100] Finally, based on the location mapping relationship, the first-order baseline simulation results are dynamically corrected using the influence coefficients of multiple sets of simulation results to obtain the node construction simulation results. The correction process requires applying the corresponding influence coefficients to the corresponding regions of the first-order baseline simulation results according to the location mapping. By adjusting the coefficients, the influence of dynamic parameters on the construction results is reflected, ultimately obtaining simulation results that balance baseline stability and dynamic flexibility.

[0101] Step S130 in the method provided in this application embodiment includes:

[0102] Extract the benchmark construction parameter subset based on the binary construction parameter set;

[0103] The node BIM model is randomly cut according to the heterogeneous base unit to obtain the heterogeneous base BIM model;

[0104] Based on the subset of benchmark construction parameters, multiple heterogeneous foundation BIM models are traversed and initialized, and construction simulation is performed to obtain first-order benchmark simulation results.

[0105] Based on the aforementioned subset of dynamic construction parameters, pattern matching is performed in the node influence pattern library to obtain multiple dynamic influence patterns.

[0106] The true values ​​of the subset of dynamic construction parameters are input into multiple dynamic influence modes to obtain multiple sets of simulation result influence coefficients;

[0107] Using the model coordinate features corresponding to the subset of dynamic construction parameters as indexes, multiple sets of simulation result influence coefficients are output in a structured manner, and a positional mapping relationship with the node BIM model is established.

[0108] Based on the location mapping relationship, the first-order baseline simulation results are dynamically corrected using multiple sets of simulation result influence coefficients to obtain the node construction simulation results.

[0109] In this embodiment of the application, in order to ensure that the simulation of complex node construction schemes can maintain basic stability and accurately respond to changes in key parameters, and to avoid the inability of a single simulation stage to take into account the needs of benchmark reference and dynamic adjustment, it is necessary to carry out the simulation through a two-stage process of benchmark simulation and dynamic correction, so as to integrate the advantages of the binary construction parameter set and heterogeneous base unit, and finally obtain accurate simulation results that fit the actual construction scenario.

[0110] In the method provided in this application embodiment, a two-stage dynamic simulation of the construction scheme is performed based on the binary construction parameter set, combined with the heterogeneous base unit and the node BIM model. Prior to this, the simulation includes:

[0111] Based on the aforementioned subset of dynamic construction parameters, prior sample data is collected, wherein the prior sample data includes at least one of historical project data and high-fidelity simulation data;

[0112] The prior sample data is dimensionally pruned based on the subset of dynamic construction parameters.

[0113] Using the sample values ​​corresponding to the subset of dynamic construction parameters described in the dimensional clipping results as independent variables, and taking multiple simulated target indicators as analysis objects, we independently modeled and obtained the node influence pattern library of the target complex node.

[0114] In this embodiment of the application, in order to avoid the dynamic parameters not being able to accurately affect the simulation results due to the lack of parameter influence mode support, it is necessary to build a node influence mode library through the process of collecting samples, cutting dimensions, and modeling analysis, so as to clarify the correlation logic between dynamic construction parameters and simulation target indicators, and ensure that the subsequent dynamic correction process is scientific and accurate.

[0115] Specifically, prior sample data is first collected based on a subset of dynamic construction parameters. The prior sample data should be selected based on the type of dynamic construction parameters and simulation requirements, and should at least cover one of the following: historical project data and high-fidelity simulation data.

[0116] Historical project data can be extracted from databases of past construction work on similar complex nodes. For example, in the construction of a large stadium's steel structure node, data on hoisting quantities at different installation elevations and construction efficiency data corresponding to different skill levels of work teams can be collected. Furthermore, high-fidelity simulation data is generated using professional simulation software. This includes data on changes in construction progress of complex electromechanical nodes under different weather influence factors and material loss data corresponding to different transportation path complexities. This ensures that the collected sample data comprehensively covers the possible range of dynamic construction parameters and actual impact scenarios.

[0117] Furthermore, after obtaining the prior sample data, the prior sample data is dimensionally pruned based on a subset of dynamic construction parameters. Specifically, dimensional pruning requires removing redundant information in the sample data that is unrelated to the dynamic construction parameters, retaining only the data dimensions related to the dynamic construction parameters and the simulated target indicators.

[0118] For example, if the subset of dynamic construction parameters includes installation elevation and weather influencing factors, and the simulated target indicators are quantity of work and cost, then during the trimming process, the installation elevation value, weather influencing factor value, corresponding quantity of work data, and corresponding cost data in the sample data will be retained, while irrelevant dimension information such as the name of the construction unit and the project start date will be removed, so as to avoid redundant data interfering with subsequent modeling and analysis, and to ensure that the trimmed sample data focuses on the core analysis dimensions.

[0119] Furthermore, after completing the dimensional clipping, the sample values ​​corresponding to the subset of dynamic construction parameters in the dimensional clipping results are used as independent variables, and multiple simulated target indicators are used as analysis objects to independently model and obtain the node influence pattern library of the target complex node.

[0120] Specifically, during the modeling process, it is necessary to construct a correlation model with dynamic construction parameters for each simulated target indicator. For example, a model can be constructed with installation elevation and weather influencing factors as independent variables and hoisting work volume as the analysis object. A cost influencing model can be constructed with team skill level and transportation route complexity as independent variables and construction cost as the analysis object.

[0121] Simultaneously, appropriate machine learning algorithms are employed during modeling to fit the relationship between parameters and indicators, forming a model that quantifies the impact of parameter changes on indicators—a dynamic influence model. Integrating all dynamic influence models creates a node influence model library.

[0122] For example, the node impact pattern library will include specific impact patterns such as "for every 5 meters increase in installation elevation, the hoisting workload increases by 15%" and "under moderate rain (impact factor 0.7), construction efficiency decreases by 30%", providing a direct and usable basis for dynamic correction in the subsequent two-stage dynamic simulation.

[0123] Furthermore, after constructing the node influence model library, the first stage of the two-stage dynamic simulation, namely the baseline simulation stage, is entered. Specifically, a subset of baseline construction parameters is first extracted based on the binary construction parameter set. The extraction process needs to screen out parameters that have a stable impact on the simulation target indicators and whose variation is minimal under different construction scenarios, such as the standard installation time of fixed-specification steel structure bolts and the number of manual labor configurations for conventional concrete foundation pouring. These parameters do not require frequent adjustments and can provide stable basic data support for the simulation, ensuring the reliability of subsequent baseline simulation results.

[0124] Furthermore, after extracting the subset of baseline construction parameters, the node BIM model is randomly cut according to the heterogeneous base unit to obtain the heterogeneous base BIM model. Specifically, the cutting must be strictly based on the previously defined heterogeneous base unit to ensure that each cut heterogeneous base BIM model can completely correspond to the construction scope and structural characteristics of a heterogeneous base unit.

[0125] For example, for a heterogeneous base unit corresponding to the installation of a single DN100 pipe section, a BIM sub-model containing the pipe section, matching fittings and surrounding fixed supports will be cut out. This ensures that the core structure of the unit is not omitted, nor are other irrelevant node areas included, thereby avoiding the disconnect between the subsequent simulation and the actual construction unit due to the deviation of the cutting range.

[0126] Furthermore, after acquiring the heterogeneous base BIM model, multiple heterogeneous base BIM models are initialized and construction simulations are performed based on a subset of baseline construction parameters to obtain first-order baseline simulation results. During initialization, the parameter values ​​in the subset of baseline construction parameters need to be matched one by one to the parameter settings of the corresponding heterogeneous base BIM model. For example, the baseline manpower configuration of "2 pipe fitters" and the baseline working hours of "1.5 working days" are entered into the heterogeneous base BIM model corresponding to pipe installation.

[0127] Meanwhile, the simulation process strictly follows the construction technology and procedures set by the benchmark parameters. For example, it simulates construction according to the standard procedures of pipeline positioning, pipe fitting connection and pressure testing. Finally, it outputs the construction results of each heterogeneous base unit under stable parameter conditions, such as the benchmark engineering quantity and benchmark cost of pipeline installation. These results are integrated to form the first-order benchmark simulation results, which provide a basic reference for subsequent dynamic correction.

[0128] Furthermore, after completing the baseline simulation phase, the second phase, the dynamic correction phase, begins. First, based on a subset of dynamic construction parameters, pattern matching is performed in the node influence pattern library to obtain multiple dynamic influence patterns.

[0129] The pattern matching process requires precise selection based on the type and characteristics of dynamic construction parameters. For example, for the spatial location parameter "installation elevation 25 meters," the dynamic pattern affecting installation elevation and hoisting work volume in the node influence pattern library will be called. In addition, for the environmental logic parameter "moderate rain (influence factor 0.7)," the dynamic pattern affecting weather influence factor and construction efficiency will be called to ensure that the obtained dynamic influence patterns can accurately reflect the influence of the corresponding parameters on the simulation results.

[0130] Furthermore, the true values ​​of subsets of dynamic construction parameters are input into multiple dynamic influence models to obtain multiple sets of simulation result influence coefficients. Specifically, the true values ​​are the actual values ​​of dynamic parameters in the current construction plan. For example, specific values ​​such as "installation elevation 25 meters" and "moderate rain weather influence factor 0.7" are input into the corresponding dynamic influence model. The model's built-in algorithm calculates and obtains quantified influence coefficients. For example, the influence coefficient for hoisting work volume corresponding to an installation elevation of 25 meters is 1.2 (meaning that the work volume is increased by 20% compared to the benchmark elevation), and the influence coefficient for construction efficiency corresponding to moderate rain weather is 0.8 (meaning that the efficiency is reduced by 20% compared to sunny days). These simulation result influence coefficients will be used to adjust the benchmark simulation results.

[0131] Furthermore, after obtaining the influence coefficients of the simulation results, multiple sets of influence coefficients of the simulation results are output in a structured manner using the model coordinate features corresponding to the subset of dynamic construction parameters as indexes, and a positional mapping relationship with the node BIM model is established.

[0132] The model coordinate features refer to the three-dimensional coordinate information of the area of ​​effect of dynamic parameters in the node BIM model. For example, a pipe with an installation height of 25 meters corresponds to the coordinate range of X=8m, Y=12m, and Z=25m in the node BIM model. The influence coefficient is output using these coordinates as an index, and the model area corresponding to the coefficient is clearly marked. For example, the hoisting quantity coefficient of 1.2 is bound to the pipe area at Z=25m to ensure that each set of influence coefficients can accurately correspond to the specific construction location in the node BIM model, avoiding mismatches between influence coefficients and locations.

[0133] Finally, based on the location mapping relationship, the first-order baseline simulation results are dynamically corrected using the influence coefficients of multiple sets of simulation results to obtain the node construction simulation results.

[0134] Specifically, the correction process requires applying the corresponding influence coefficients to the relevant regions of the first-order baseline simulation results according to the location mapping. For example, in the pipeline region with Z=25m, the baseline hoisting quantity is multiplied by an influence coefficient of 1.2 to obtain the corrected actual hoisting quantity. In addition, in the work area affected by moderate rain, the baseline construction efficiency is multiplied by an influence coefficient of 0.8 to obtain the corrected actual construction efficiency.

[0135] This step, through the aforementioned regional and precise corrections, ensures that the final node construction simulation results retain the stability of the benchmark simulation while incorporating the actual impact of dynamic parameters, making them more closely resemble the real construction scenarios of complex nodes and providing a reliable basis for construction scheme optimization and decision-making.

[0136] The embodiments of this application, through the above specific implementation methods, achieve the following technical effects:

[0137] This application proposes a BIM-based dynamic simulation method for construction schemes of complex building nodes. First, it obtains the node BIM model of the target complex node. Then, combining prior node knowledge, it decomposes the model based on construction operability, extracting the smallest construction unit that meets standardized process constraints and is repeatably measurable. Next, it defines a common base level containing material hierarchy information and process list information. Then, based on the common base level, it meshes the node BIM model, obtains multi-dimensional feature vectors for the mesh, and uses an unsupervised clustering algorithm to divide the mesh into multiple construction feature clusters. Heterogeneous base units are defined based on these construction feature clusters, and the inherent parameters of the units are labeled. Subsequently, it obtains the simulation target indicators and construction scheme parameters, iterates and combines them to form correlation analysis groups, and divides the base units through correlation analysis. A binary construction parameter set is constructed by combining a subset of quasi- and dynamic construction parameters. Simultaneously, prior sample data from historical projects or high-fidelity simulations are collected based on the dynamic construction parameter set. After dimensional clipping, independent models are built using parameter sample values ​​as independent variables and simulation target indicators as analysis objects, constructing a node influence mode library. Next, a baseline construction parameter subset is extracted based on the binary construction parameter set. A heterogeneous base BIM model is obtained by clipping the node BIM model according to heterogeneous base elements. After initialization, construction simulation is performed to obtain first-order baseline simulation results. Finally, the node influence mode library is called to match dynamic influence modes, inputting the true values ​​of dynamic parameters to calculate influence coefficients. A position mapping relationship is established by combining model coordinate characteristics, and the first-order baseline simulation results are corrected using the influence coefficients, ultimately obtaining the node construction simulation results.

[0138] The method provided in this application, through the technical solution of "BIM model layering and heterogeneous unit definition - dynamic division of construction parameters and construction of influence mode library - two-stage dynamic simulation and result correction", solves the problems of insufficient accuracy due to rough model processing, indiscriminate parameter processing that cannot adapt to dynamic influence, and lack of targeted data support in the traditional construction simulation of complex building nodes. It improves the accuracy, flexibility and reliability of construction scheme simulation of complex nodes, and provides scientific data support for construction scheme optimization and adjustment, resource allocation planning and construction risk prediction. It is applicable to construction simulation scenarios of various complex nodes in large and complex building projects.

[0139] Example 2, as shown in the appendix Figure 2As shown, based on the inventive concept of the BIM-based dynamic simulation method for construction schemes of complex building nodes provided in Embodiment 1, this application also provides a BIM-based dynamic simulation system for construction schemes of complex building nodes, specifically including:

[0140] The region division and unit definition module 01 is used to adaptively divide the construction area of ​​the node BIM model based on multidimensional feature clustering, and define heterogeneous base units based on the adaptive division results.

[0141] The construction parameter binary module 02 is used to dynamically divide the construction scheme parameters based on the influence mode according to the heterogeneous base unit to obtain a binary construction parameter set, wherein the binary construction parameter set includes a subset of baseline construction parameters and a subset of dynamic construction parameters.

[0142] The two-stage dynamic simulation module 03 is used to perform a two-stage dynamic simulation of the construction scheme based on the binary construction parameter set, combined with the heterogeneous base unit and the node BIM model, and to obtain the node construction simulation results.

[0143] In one embodiment, the region division and unit definition module 01 is further used for:

[0144] Obtain the node BIM model of the target complex node, and analyze and determine the common base level of the node BIM model; based on the common base level, perform meshing on the node BIM model to obtain the mesh BIM model; traverse and obtain the multi-dimensional feature vector of the mesh BIM model, and combine unsupervised clustering algorithm to divide the multiple mesh BIM models into multiple construction feature clusters; define multiple heterogeneous base elements according to the multiple construction feature clusters, and mark the element intrinsic parameters of the heterogeneous base elements.

[0145] Furthermore, the region division and unit definition module 01 also includes:

[0146] The node BIM model is decomposed based on construction operability by combining the prior knowledge of the target complex nodes; according to the model decomposition results, the smallest construction unit that meets the standardized process constraints and can be repeatedly measured is extracted, and the common base level is defined accordingly; wherein, the common base level includes coupled material level information and process list information.

[0147] Furthermore, the region division and unit definition module 01 also includes:

[0148] The inherent parameters of the unit include at least the benchmark working hours, benchmark manpower configuration, benchmark machine configuration, and benchmark material consumption.

[0149] Furthermore, the region division and unit definition module 01 also includes:

[0150] Multidimensional features include at least geometric features, spatial features, technological features, and logical features.

[0151] In one embodiment, the construction parameter binary module 02 is also used for:

[0152] The process involves obtaining simulated target indicators for complex nodes and parsing construction scheme information to extract construction scheme parameters. The simulated target indicators include at least one of two categories: quantity indicators and cost indicators. The process then iterates through the construction scheme parameters and randomly combines them with the simulated target indicators to obtain multiple correlation analysis groups. Correlation analysis is performed on these multiple correlation analysis groups, and the construction scheme parameters of the multiple correlation analysis groups whose correlation analysis results satisfy a preset significance constraint are identified as the dynamic construction parameter subset. Finally, a reverse selection process is performed between the dynamic construction parameter subset and the construction scheme parameters to determine the baseline construction parameter subset.

[0153] In one embodiment, the two-stage dynamic simulation module 03 is also used for:

[0154] Based on the binary construction parameter set, the baseline construction parameter subset is extracted; the node BIM model is randomly truncated according to the heterogeneous base unit to obtain a heterogeneous base BIM model; based on the baseline construction parameter subset, multiple heterogeneous base BIM models are traversed and initialized, and construction simulation is performed to obtain first-order baseline simulation results. Based on the dynamic construction parameter subset, pattern matching is performed in the node influence pattern library to obtain multiple dynamic influence patterns; the truth values ​​of the dynamic construction parameter subset are input to multiple dynamic influence patterns to obtain multiple sets of simulation result influence coefficients; using the model coordinate features corresponding to the dynamic construction parameter subset as indexes, multiple sets of simulation result influence coefficients are structured and output, and a positional mapping relationship with the node BIM model is established; based on the positional mapping relationship, the first-order baseline simulation results are dynamically corrected through multiple sets of simulation result influence coefficients to obtain the node construction simulation results.

[0155] Furthermore, the two-stage dynamic simulation module 03 also includes:

[0156] Based on the subset of dynamic construction parameters, prior sample data is collected, wherein the prior sample data includes at least one of historical project data and high-fidelity simulation data; the prior sample data is dimensionally truncated based on the subset of dynamic construction parameters; the sample values ​​corresponding to the subset of dynamic construction parameters in the dimensional truncated result are used as independent variables, and multiple simulated target indicators are used as analysis objects to independently model and obtain a node influence pattern library of target complex nodes.

[0157] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0158] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0159] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for dynamic simulation of construction scheme of complex nodes of buildings based on BIM, characterized in that, The method comprises the following steps: Adaptive division of construction area based on multi-dimensional feature clustering is performed on a node BIM model, and heterogeneous base units are defined based on the adaptive division result; According to the heterogeneous base units, dynamic division of construction scheme parameters is performed based on influence modes, and a two-part construction parameter set is obtained, wherein the two-part construction parameter set comprises a reference construction parameter subset and a dynamic construction parameter subset; According to the two-part construction parameter set, two-stage dynamic simulation of the construction scheme is performed in combination with the heterogeneous base units and the node BIM model, and a node construction simulation result is obtained; According to the two-part construction parameter set, two-stage dynamic simulation of the construction scheme is performed in combination with the heterogeneous base units and the node BIM model, and a node construction simulation result is obtained, The method comprises the following steps: The reference construction parameter subset is extracted based on the two-part construction parameter set; The node BIM model is randomly cut according to the heterogeneous base units, and a heterogeneous base BIM model is obtained; According to the reference construction parameter subset, a plurality of heterogeneous base BIM models are initialized and simulated, and a first-order reference simulation result is obtained; The method further comprises the following steps: Based on the dynamic construction parameter subset, mode matching and calling are performed in a node influence mode library, and a plurality of dynamic influence modes are obtained; The true values of the dynamic construction parameter subset are respectively input into a plurality of dynamic influence modes, and a plurality of sets of simulation result influence coefficients are obtained; Taking the model coordinate features corresponding to the dynamic construction parameter subset as indexes, a plurality of sets of simulation result influence coefficients are structured and output, and a position mapping relationship with the node BIM model is established; According to the position mapping relationship, the first-order reference simulation result is dynamically corrected through a plurality of sets of simulation result influence coefficients, and the node construction simulation result is obtained.

2. The BIM-based construction complex node construction plan dynamic simulation method of claim 1, wherein, Adaptive division of construction area based on multi-dimensional feature clustering is performed on a node BIM model, and heterogeneous base units are defined based on the adaptive division result, comprising: A node BIM model of a target complex node is obtained, and a common base level of the node BIM model is analyzed and determined; Based on the common base level, a grid BIM model is obtained by dividing the node BIM model into grids; Multi-dimensional feature vectors of the grid BIM model are obtained by traversal, and a plurality of construction feature clusters are divided from a plurality of grid BIM models by combining an unsupervised clustering algorithm; A plurality of heterogeneous base units are defined according to a plurality of construction feature clusters, and unit inherent parameters of the heterogeneous base units are marked.

3. The BIM-based construction complex node construction plan dynamic simulation method of claim 1, wherein, A node BIM model of a target complex node is obtained, and a common base level of the node BIM model is analyzed and determined, comprising: The node BIM model is decomposed based on construction operability in combination with node prior knowledge of a target complex node; According to the model decomposition result, a minimum construction unit that meets standardized process constraints and can be repeatedly metered is extracted, and the common base level is defined correspondingly; The common base level comprises coupled material level information and process list information.

4. The BIM-based construction complex node construction plan dynamic simulation method of claim 2, wherein, The unit inherent parameters at least include reference working hours, reference labor configuration, reference mechanical configuration and reference material consumption.

5. The BIM-based construction complex node construction plan dynamic simulation method of claim 1, wherein, The multi-dimensional features include at least geometric features, spatial features, process features and logical features.

6. The BIM-based construction complex node construction plan dynamic simulation method of claim 1, wherein, According to the heterogeneous base unit, the construction scheme parameters are dynamically divided based on influence modes to obtain a two-part construction parameter set, wherein the two-part construction parameter set includes a benchmark construction parameter subset and a dynamic construction parameter subset, and includes: Obtaining simulation target indicators of the target complex node, and analyzing construction scheme information to extract the construction scheme parameters, wherein the simulation target indicators include at least one of an engineering quantity index and an engineering cost index; Iterating the construction scheme parameters, and randomly combining the simulation target indicators to obtain a plurality of correlation analysis groups; Performing correlation analysis on the plurality of correlation analysis groups, and determining the construction scheme parameters of the correlation analysis groups that satisfy a preset significance constraint as the dynamic construction parameter subset; Combining the dynamic construction parameter subset and the construction scheme parameters to perform reverse selection to determine the benchmark construction parameter subset.

7. The BIM-based construction complex node construction plan dynamic simulation method of claim 1, wherein, According to the two-part construction parameter set, combining the heterogeneous base unit and the node BIM model to perform two-stage dynamic simulation on the construction scheme, and before that, including: According to the dynamic construction parameter subset, collecting prior sample data, wherein the prior sample data includes at least one of historical project data and high-fidelity simulation data; Based on the dynamic construction parameter subset, dimensionally cutting the prior sample data; Taking the sample values corresponding to the dynamic construction parameter subset in the dimensionally cutting result as independent variables, and respectively taking a plurality of simulation target indicators as analysis objects to independently model, to obtain a node influence mode library of the target complex node.

8. A BIM-based construction scheme dynamic simulation system for a complex node of a building, characterized in that, The system is used to perform the BIM-based construction scheme dynamic simulation method of a complex node of a building according to any one of claims 1-7, and the system includes: A region division and unit definition module is configured to perform adaptive division of a construction region of a node BIM model based on multi-dimensional feature clustering, and define a heterogeneous base unit based on an adaptive division result; A construction parameter two-part division module is configured to perform dynamic division of construction scheme parameters based on influence modes according to the heterogeneous base unit to obtain a two-part construction parameter set, wherein the two-part construction parameter set includes a benchmark construction parameter subset and a dynamic construction parameter subset; A two-stage dynamic simulation module is configured to perform two-stage dynamic simulation on a construction scheme according to the two-part construction parameter set, in combination with the heterogeneous base unit and the node BIM model, to obtain a node construction simulation result.

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