A railway construction simulation model generation method based on full-line design parameters

Abstract

The application discloses a railway construction simulation model generation method based on full-line design parameters, relates to the technical field of model simulation, collects line track geometric parameters, geological exploration data, bridge and tunnel structure parameters, construction mechanical performance indexes and environmental constraint conditions, constructs a multi-source heterogeneous database, constructs full-line design parameters after spatial coordinate unification and data cleaning, establishes a time and space dependency relationship of construction elements based on a line section topological structure of the railway, generates an initial construction logic network, optimizes the construction logic network according to construction efficiency, resource scheduling rules and dynamic constraint conditions, defines parallel construction events in a railway construction process, maps the full-line design parameters and the construction logic network into a three-dimensional visual simulation model of railway construction through a parameterized modeling engine, introduces real-time railway construction data, predicts a construction delay probability of the railway construction, and determines whether to make construction process adjustment and construction resource redistribution.

Description

Technical Field

[0001] This invention relates to the field of model simulation technology, specifically a method for generating railway construction simulation models based on full-line design parameters. Background Technology

[0002] In the field of railway construction, traditional construction management and design methods often rely on manual experience. Typically, the acquisition and organization of design parameters for the entire railway line depend on various data sources, such as track geometry parameters, geological exploration data, and bridge and tunnel structural parameters. However, these data are often multi-source and heterogeneous, making effective integration and analysis difficult. Furthermore, the establishment and optimization of construction logic in the railway construction process have shortcomings, and the definition and simulation of different construction events lack effective monitoring mechanisms. Therefore, existing technologies have the following deficiencies:

[0003] 1. Low data processing efficiency, making it difficult to effectively integrate multi-source heterogeneous data;

[0004] 2. The establishment and optimization process of the construction logic has drawbacks, resulting in low construction efficiency;

[0005] 3. The lack of effective supervision over the execution definition and simulation of different construction events in the railway construction process has led to difficulties in predicting the risks that exist in the construction process, resulting in delays in the construction period. Summary of the Invention

[0006] To address the aforementioned problems, the present invention aims to provide a method for generating railway construction simulation models based on the design parameters of the entire railway line.

[0007] The objective of this invention can be achieved through the following technical solution: a method for generating a railway construction simulation model based on full-line design parameters, comprising the following steps:

[0008] Step S1: Collect track geometry parameters, geological exploration data, bridge and tunnel structural parameters, construction machinery performance indicators and environmental constraints, construct a multi-source heterogeneous database, and perform spatial coordinate unification and data cleaning on all data in the multi-source heterogeneous database to construct the design parameters for the entire line.

[0009] Step S2: Based on the segmented topology of the railway line, establish the spatiotemporal dependencies of construction elements, thereby generating an initial construction logic network, and optimize the construction logic network according to construction efficiency, resource scheduling rules and dynamic constraints.

[0010] Step S3: Define parallel construction events in the railway construction process, and map the entire line design parameters and construction logic network into a three-dimensional visualization simulation model of railway construction through a parametric modeling engine.

[0011] Step S4: Introduce real-time railway construction data into the three-dimensional visualization simulation model to predict the probability of construction delays and decide whether to adjust the construction procedures and reallocate construction resources.

[0012] Furthermore, the process of collecting track geometry parameters, geological exploration data, bridge and tunnel structural parameters, construction machinery performance indicators, and environmental constraints to construct a multi-source heterogeneous database includes:

[0013] Obtain BIM files and CAD drawings for railway construction design, extract parametric design files from BIM files and CAD drawings, and obtain track geometry parameters after processing.

[0014] The system integrates ground-penetrating radar detection reports, borehole exploration data, and remote sensing images for translation and interpretation. It also conducts real-time geological exploration of the railway construction area using sensors to obtain geological exploration data.

[0015] The structural parameters of the bridge and tunnel were obtained by analyzing the bridge and tunnel structure using structural design software.

[0016] The performance indicators of construction machinery can be obtained from the corresponding technical manuals of the construction machinery.

[0017] Environmental constraints include restricted construction periods, ecological protection zones, extreme weather, and other uncontrollable factors;

[0018] A data source file is constructed for each of the track geometry parameters, geological exploration data, bridge and tunnel structural parameters, construction machinery performance indicators, and environmental constraints. File indexes are assigned to these files, and all data source files are integrated into a pre-built database to construct a multi-source heterogeneous database. Each data source file creates a data temporary storage area within the multi-source heterogeneous database.

[0019] Furthermore, the process of unifying spatial coordinates and cleaning all data within the multi-source heterogeneous database to construct the entire line design parameters includes:

[0020] Set up a first operation period to unify the spatial coordinates of all data in the multi-source heterogeneous database; set up a second operation period to clean the data of each data source file in the multi-source heterogeneous database that has completed spatial coordinate unification, and convert the data source files in each data temporary storage area in the multi-source heterogeneous database into standard data files.

[0021] All standard data files are integrated to construct the full-line design parameters, which are used to characterize all line construction-related data information at each time point, each construction stage, and each construction location during railway construction.

[0022] Furthermore, based on the segmented topology of the railway line, the process of establishing the spatiotemporal dependencies of construction elements and generating the initial construction logic network includes:

[0023] Obtain the overall construction route map for the railway construction and divide the railway line into several construction sections;

[0024] Establish spatial adjacency relationships between construction sections, construct the line segment topology corresponding to railway construction through graphics technology, define construction elements within each construction section, and use the construction elements as topology nodes in the corresponding line segment topology of the railway.

[0025] Define the spatiotemporal dependencies between construction elements and use these dependencies as topological edges in the corresponding railway line segment topology.

[0026] Once all topological nodes and edges in the railway line segment topology are defined, the topological edge paths between construction elements are associated with the railway line topology segment structure according to the execution order of the railway construction logic, thereby constructing the initial construction logic network.

[0027] Furthermore, the process of optimizing the construction logic network based on construction efficiency, resource scheduling rules, and dynamic constraints includes:

[0028] Construct network optimization node one, network optimization node two, and network optimization node three;

[0029] By analyzing whether the construction efficiency of the network optimization node affects the railway construction, if so, dynamic correction of the process schedule and optimization of the parallel pipeline are carried out; if not, no operation is performed.

[0030] By analyzing the impact of resource scheduling rules on railway construction through network optimization node two, if the progress of railway construction under the current resource scheduling rules does not meet the expected progress, resource conflict resolution and resource utilization optimization will be carried out to achieve flexible resource allocation; otherwise, no operation will be performed.

[0031] By embedding dynamic constraints into the construction logic network through network optimization node three, the initial construction logic network is optimized.

[0032] Furthermore, defining parallel construction events in the railway construction process, and mapping the entire line design parameters and construction logic network into a 3D visualization simulation model of railway construction through a parametric modeling engine includes:

[0033] The parallel types of parallel construction events in the railway construction process are defined, and the parallel types are divided into spatial parallelism, process parallelism and resource-driven parallelism. Two construction elements with spatial adjacency in the construction logic network are respectively taken as construction events.

[0034] If two construction elements belong to any parallel type, then the two construction events corresponding to the two construction elements are determined to be parallel construction events; otherwise, they are determined not to be parallel construction events.

[0035] Configure the model parameters when using the parametric modeling engine to build an initial 3D railway track model. Then, use the parametric modeling engine to map all the line construction-related data information, representing each time point, each construction stage, and each construction location during railway construction, from the full line design parameters to the corresponding time segments, construction segments, and location segments pre-built in the 3D railway track model. Define and map the construction process status of each construction element included in the construction logic network, and mark different model representation colors and process progress bars for different construction process statuses.

[0036] Then, a three-dimensional visualization simulation model corresponding to the current railway construction is constructed.

[0037] Furthermore, the correspondence between the construction process status and the model's displayed colors is as follows:

[0038] The status of construction procedures includes not started, in progress, and completed.

[0039] When the construction process status is "not started", the model will be displayed in red.

[0040] When the construction process is in progress, the model will be displayed in yellow.

[0041] When the construction process is in the completed state, the model will be displayed in green.

[0042] The progress range of the process progress bar is 0 to 100%. When it is 0, the construction process status is not started. When it is 100%, the construction process status is completed. When it is any other progress value, the construction process status is in progress.

[0043] Furthermore, the process of introducing real-time railway construction data into a 3D visualization simulation model to predict the probability of construction delays and determine whether to adjust construction procedures and reallocate construction resources includes:

[0044] Real-time railway construction data is introduced into a 3D visualization simulation model, which then analyzes the ongoing construction section of the railway to obtain visualized construction data for the current construction section.

[0045] The visualized construction data of the current construction section is processed using the Monte Carlo simulation algorithm and Bayesian prediction network to predict the probability of construction delay in railway construction. The probability of construction delay is denoted as P, and a decision threshold is set and denoted as JC.

[0046] If P≥JC, then it is decided to adjust the construction procedures and reallocate construction resources.

[0047] If P < JC, then no operation is performed.

[0048] Compared with existing technologies, the beneficial effects of this invention are as follows: By constructing a multi-source heterogeneous database, it effectively integrates various data sources such as track geometry parameters, geological exploration data, and bridge and tunnel structural parameters, thereby improving data processing efficiency. Based on the segmented topology of the railway line, it establishes the spatiotemporal dependencies between construction elements and provides an effective monitoring method during construction by optimizing the construction logic network. By defining parallel construction events in the railway construction process and combining them with a parametric modeling engine, it realizes a three-dimensional visualization simulation model of railway construction, which helps to predict risks and delays during construction. It introduces real-time railway construction data into the three-dimensional visualization simulation model to predict the probability of construction delays and to adjust construction procedures and reallocate construction resources, thereby improving the overall efficiency and quality of railway construction and effectively avoiding delays in the construction period. Attached Figure Description

[0049] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0050] like Figure 1 As shown, a method for generating a railway construction simulation model based on the design parameters of the entire line includes the following steps:

[0051] Step S1: Collect track geometry parameters, geological exploration data, bridge and tunnel structural parameters, construction machinery performance indicators and environmental constraints, construct a multi-source heterogeneous database, and perform spatial coordinate unification and data cleaning on all data in the multi-source heterogeneous database to construct the design parameters for the entire line.

[0052] Step S2: Based on the segmented topology of the railway line, establish the spatiotemporal dependencies of construction elements, thereby generating an initial construction logic network, and optimize the construction logic network according to construction efficiency, resource scheduling rules and dynamic constraints.

[0053] Step S3: Define parallel construction events in the railway construction process, and map the entire line design parameters and construction logic network into a three-dimensional visualization simulation model of railway construction through a parametric modeling engine.

[0054] Step S4: Introduce real-time railway construction data into the three-dimensional visualization simulation model to predict the probability of construction delays and decide whether to adjust the construction procedures and reallocate construction resources.

[0055] It should be further explained that, in the specific implementation process, the process of collecting track geometry parameters, geological exploration data, bridge and tunnel structural parameters, construction machinery performance indicators, and environmental constraints to construct a multi-source heterogeneous database includes:

[0056] Obtain BIM files and CAD drawings for railway construction design, extract parametric design files from BIM files and CAD drawings. Parametric design files are used to record point cloud data of railway construction. Obtain track geometry parameters by reverse modeling through laser scanning point cloud data.

[0057] The track geometry parameters include the radius of the track plane curve, the longitudinal slope, the superelevation, the track gauge, and the sleeper arrangement density;

[0058] The system integrates ground-penetrating radar detection reports, borehole exploration data, and remote sensing images as files to be parsed, performs real-time translation and interpretation of these files, and conducts real-time geological exploration of the railway construction area by deploying several types of geological monitoring-related sensors, thereby obtaining geological exploration data.

[0059] Geological exploration data includes stratigraphic lithology distribution, groundwater level, soil mechanical parameters (such as shear strength and compression modulus), and geological hazard risk zones;

[0060] The bridge and tunnel structure is analyzed using structural design software, and the finite element model parameters of the bridge and tunnel structure are exported. The component attribute table is extracted from the finite element model parameters, and the bridge and tunnel structure parameters are obtained by analyzing the component attribute table.

[0061] Bridge and tunnel structural parameters include bridge span, pier coordinates, pile foundation depth, tunnel cross-sectional shape, support type (anchor bolts, shotcrete), and surrounding rock grade.

[0062] The performance indicators of construction machinery include the type of machinery, working efficiency, and energy consumption parameters.

[0063] The performance indicators of the construction machinery are obtained from the technical manuals corresponding to the construction machinery.

[0064] Environmental constraints include restricted construction periods, ecological protection zones, extreme weather, and other uncontrollable factors;

[0065] A data source file is constructed for each of the track geometry parameters, geological exploration data, bridge and tunnel structural parameters, construction machinery performance indicators, and environmental constraints. A corresponding file index is assigned to each data source file, and the file index serves as a unique identifier for the data source file.

[0066] All data source files with assigned file indexes are integrated into a pre-built database, which is then transformed into a multi-source heterogeneous database. A data staging area is created for each data source file corresponding to a file index within the multi-source heterogeneous database.

[0067] It should be further explained that, in the specific implementation process, the process of unifying the spatial coordinates and cleaning the data of all data in the multi-source heterogeneous database, and then constructing the design parameters for the entire line, includes:

[0068] A first operation period is set and denoted as T1, where T1 = [ta, tb], and ta is the start time of the first operation period, and tb is the end time of the first operation period. Within the first operation period, spatial coordinate unification is performed on all data in the multi-source heterogeneous database. The content of spatial coordinate unification is as follows:

[0069] Construct a coordinate system for railway construction. Extract the corresponding data source file for each file index from a multi-source heterogeneous database. Determine whether the data space coordinate format of each data source file is within the railway construction coordinate system. If it is, no operation is performed. If not, perform coordinate system transformation on the data space coordinate format of the data source file to transform the data source file corresponding to each file index into a unified railway construction coordinate system.

[0070] A second operation period is set up and denoted as T2, where T2 = [tc, td], tc is the start time of the second operation period, and td is the end time of the second operation period. During the second operation period, data cleaning is performed on each data source file in the multi-source heterogeneous database that has completed spatial coordinate unification. Through data cleaning, erroneous data is corrected, redundant data is deleted, and missing data is imputed. In this way, the data source file corresponding to each data temporary storage area in the multi-source heterogeneous database is converted into the corresponding standard data file.

[0071] All standard data files are integrated to construct the full-line design parameters. These full-line design parameters are used to characterize all line construction-related data information at each time point, each construction stage, and each construction location during railway construction, serving as important parameter information for railway construction.

[0072] It should be further explained that, in the specific implementation process, the process of establishing the spatiotemporal dependencies of construction elements based on the segmented topology of the railway line, and then generating the initial construction logic network, includes:

[0073] Obtain the overall construction route map for railway construction. The overall construction route map is used to record the construction direction of the railway line, the total length of the line, and various construction details parameters. Set the section distance, divide the railway line into several construction sections according to the section distance and the total length of the line, and associate and bind a construction project identifier to each construction section.

[0074] Establish spatial adjacency relationships between construction sections, and construct the line segment topology corresponding to railway construction through graphics technology. The line segment topology is used to represent the topological mapping relationship of each construction section in the railway line.

[0075] Define the construction elements within each construction segment. Construction elements include, but are not limited to, track slab laying, bridge pier pouring, tunnel excavation, tunnel support, and roadbed compaction. These construction elements are treated as topological nodes in the corresponding railway line segment topology.

[0076] Define the spatiotemporal dependencies between construction elements, including hard dependencies, soft dependencies, and resource dependencies, and use the spatiotemporal dependencies between construction elements as topological edges in the corresponding railway line segment topology.

[0077] Examples of hard dependencies, soft dependencies, and resource dependencies in the spatiotemporal dependencies are illustrated below:

[0078] Hard dependency: There is a mandatory order in which construction elements are constructed;

[0079] For example, in the process of "subgrade compaction → track laying", the subsequent track laying can only proceed after the subgrade compaction is completed first.

[0080] Soft dependency: There is no specific order of construction between construction elements, and they can be carried out simultaneously;

[0081] For example, "bridge erection and adjacent roadbed construction" can be carried out simultaneously when there are sufficient construction resources;

[0082] Resource dependence: Conflict constraints between construction-related machinery and equipment or construction personnel;

[0083] For example, the same bridge erecting machine cannot carry out bridge erection operations in two construction sections at the same time;

[0084] After defining all topological nodes and edges in the corresponding railway line segment topology, the construction logic of the railway construction is executed in the order of construction logic. The topological edge directions between construction elements are associated with the railway line topology segment structure, thereby constructing the initial construction logic network.

[0085] It should be further explained that, in the specific implementation process, the optimization of the construction logic network based on construction efficiency, resource scheduling rules, and dynamic constraints includes:

[0086] Construct network optimization node one, network optimization node two, and network optimization node three;

[0087] By analyzing whether the construction efficiency of the network optimization node affects railway construction, if so, dynamic correction of the process duration and optimization of the parallel pipeline are performed; otherwise, no operation is performed. The specific process of dynamic correction of the process duration and optimization of the parallel pipeline is as follows:

[0088] Dynamic correction of process duration includes mechanical efficiency modeling and adaptive adjustment of process time;

[0089] The content of mechanical efficiency modeling is as follows:

[0090] A dynamic model of mechanical efficiency is constructed based on the performance indicators of construction machinery (such as the daily laying volume of track laying machine and concrete pumping rate) and real-time operating data (such as GPS trajectory and fuel consumption). An environmental degradation factor (such as a 15% decrease in mechanical power in plateau areas) is introduced to correct the theoretical construction period.

[0091] The adaptive adjustment of process time includes:

[0092] If the actual progress deviation of a certain process exceeds the threshold (e.g., ±10%), the calculation of time parameters for subsequent processes will be triggered. Example: If the daily progress of tunnel excavation drops from 5m to 3m due to the unexpected hardness of the rock strata, the construction period will be automatically extended and related processes will be adjusted.

[0093] Parallel pipeline optimization includes process decomposition and parallelization, as well as pipeline cycle time balancing;

[0094] The content of process decomposition and parallel processing is as follows:

[0095] Break down long-cycle processes into sub-tasks (e.g., "bridge erection" is broken down into "beam transport → hoisting → welding"), allow some sub-tasks to run in parallel, identify bottleneck resources, and prioritize the allocation of resources to critical chain processes.

[0096] The content of assembly line cycle balancing includes:

[0097] Calculate the difference in cycle time between adjacent processes (e.g., roadbed compaction requires 2 days / section, track laying requires 1.5 days / section), and achieve cycle time synchronization by adjusting resource allocation (e.g., increasing the number of road rollers);

[0098] By analyzing the impact of resource scheduling rules on railway construction through network optimization node two, if the progress of railway construction under the current resource scheduling rules does not meet the expected progress, resource conflict resolution and resource utilization optimization will be carried out to achieve flexible resource allocation; otherwise, no operation will be performed.

[0099] The specific processes of resource conflict resolution, resource utilization optimization, and flexible resource allocation are as follows:

[0100] The content of resource conflict resolution includes: conducting resource competition analysis, constructing a resource-process correlation matrix, and identifying conflict periods for shared resources (such as concrete mixer trucks and bridge erecting machines). For example, if two bidding sections apply for the same bridge erecting machine at the same time, a conflict warning is triggered.

[0101] Define priority rules, allocate resources according to the importance of the construction section or the urgency of the contract period, and use dynamic scheduling algorithms to generate the optimal resource scheduling scheme under the construction section in order to resolve resource conflicts under the current construction section.

[0102] The optimization of resource utilization includes: analyzing the peak and valley loads of machinery / personnel through resource histograms, and diverting high-load periods (such as staggered construction); Example: If the daily production capacity of a concrete mixing plant is 1000m³, and the demand on a certain day reaches 1200m³, the model suggests prefabricating some components in advance or adding a temporary mixing plant;

[0103] The content of flexible resource allocation includes: defining resource flexibility strategies (such as leasing spare machinery and temporarily hiring workers) and dynamically activating them based on schedule deviations.

[0104] By embedding dynamic constraints into the construction logic network through network optimization node three, the dynamic constraints include a weather-efficiency relationship rule library constructed based on the real-time weather conditions in the railway construction area, dynamic construction window adjustment selected based on the output results of the weather-efficiency relationship rule library, and a risk-contingency plan rule library constructed based on whether there are any sudden risk events in the construction area.

[0105] The weather-efficiency relationship rule base is explained as follows:

[0106] Access real-time meteorological API data and define a rule base for weather-work efficiency relationships (such as "heavy rain → roadbed construction stoppage" and "strong wind → high-altitude operations prohibited").

[0107] The instructions for adjusting the dynamic construction window are as follows:

[0108] When an event occurs that affects the current construction progress, the original type of construction work is changed. For example, when it rains, the original outdoor work is changed to indoor work.

[0109] The explanation of the risk-contingency plan rule base is as follows:

[0110] Predefine typical sudden risk events (such as mechanical failure, geological disaster, supply chain disruption) and their impact parameters (such as repair time, cost of alternative solutions);

[0111] Example: A tunnel boring machine malfunction caused a 3-day work stoppage. The model automatically called up the backup equipment and recalculated the critical path.

[0112] By analyzing construction efficiency and resource scheduling rules, and embedding dynamic constraints into the construction logic network, the construction logic network was further improved.

[0113] It should be further explained that, in the specific implementation process, the process of defining parallel construction events in the railway construction workflow and mapping the entire line design parameters and construction logic network into a three-dimensional visualization simulation model of railway construction through a parametric modeling engine includes:

[0114] The parallel types of parallel construction events in the railway construction process are defined, and the parallel types are divided into spatial parallelism, process parallelism and resource-driven parallelism. Two construction elements with spatial adjacency in the construction logic network are taken as construction events to be judged as whether they can be executed.

[0115] If two construction elements belong to any of the parallel types of spatial parallelism, process parallelism, and resource-driven parallelism, then the two construction events corresponding to the two construction elements are determined to be parallel construction events; otherwise, they are determined not to be parallel construction events.

[0116] Examples of parallel types for parallel construction events are illustrated below:

[0117] Parallel construction in space: independent construction in different sections at the same time, such as bridge erection in section A and tunnel excavation in section B;

[0118] Parallel operation: Multiple disciplines work together within the same section, such as: track slab laying and catenary column installation are carried out simultaneously;

[0119] Resource-driven parallelism: Time-sharing multiplexing under shared resource constraints, such as the same bridge erecting machine alternating operations in different sections;

[0120] Configure the model parameters when using the parametric modeling engine to build the initial three-dimensional railway track model. Then, use the parametric modeling engine to map all the line construction-related data information, which represent each time point, each construction stage, and each construction location during railway construction, from the full line design parameters to the corresponding time segments, construction segments, and location segments pre-built in the three-dimensional railway track model.

[0121] Define and map the construction process status of each construction element in the construction logic network. The construction process status includes not started, in progress, and completed. Different model representation colors and process progress bars are marked for different construction process statuses.

[0122] The correspondence between the construction process status and the model's color representation is as follows:

[0123] When the construction process status is "not started", the model will be displayed in red.

[0124] When the construction process is in progress, the model will be displayed in yellow.

[0125] When the construction process is in the completed state, the model will be displayed in green.

[0126] The progress range of the process progress bar is 0 to 100%. When it is 0, the construction process status is not started. When it is 100%, the construction process status is completed. When it is any other progress value, the construction process status is in progress.

[0127] Once the construction process status of each construction element in the construction logic network has been mapped, a three-dimensional visualization simulation model corresponding to the current railway construction is constructed.

[0128] It should be further explained that, in the specific implementation process, the process of introducing real-time railway construction data into the 3D visualization simulation model to predict the probability of construction delays and to decide whether to adjust construction procedures and reallocate construction resources includes:

[0129] Real-time railway construction data is introduced into a 3D visualization simulation model, which then analyzes the ongoing construction section of the railway to obtain visualized construction data for the current construction section.

[0130] The visualized construction data of the current construction section is processed using the Monte Carlo simulation algorithm and Bayesian prediction network to predict the probability of construction delay in railway construction. The probability of construction delay is denoted as P, and a decision threshold is set and denoted as JC.

[0131] If P≥JC, then it is decided to adjust the construction procedures and reallocate construction resources.

[0132] If P < JC, then no operation is performed.

[0133] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for generating a railway construction simulation model based on full-line design parameters, characterized in that, Includes the following steps: Step S1: Collect track geometry parameters, geological exploration data, bridge and tunnel structural parameters, construction machinery performance indicators and environmental constraints, construct a multi-source heterogeneous database, and perform spatial coordinate unification and data cleaning on all data in the multi-source heterogeneous database to construct the design parameters for the entire line. Step S2: Based on the segmented topology of the railway line, establish the spatiotemporal dependencies of construction elements, thereby generating an initial construction logic network, and optimize the construction logic network according to construction efficiency, resource scheduling rules and dynamic constraints. Step S3: Define parallel construction events in the railway construction process, and map the entire line design parameters and construction logic network into a three-dimensional visualization simulation model of railway construction through a parametric modeling engine. Step S4: Introduce real-time railway construction data into the three-dimensional visualization simulation model to predict the probability of construction delays and decide whether to adjust the construction procedures and reallocate construction resources. The process of establishing the spatiotemporal dependencies of construction elements based on the segmented topology of railway lines, and then generating the initial construction logic network, includes: Obtain the overall construction route map for the railway construction and divide the railway line into several construction sections; Establish spatial adjacency relationships between construction sections, construct the line segment topology corresponding to railway construction through graphics technology, define construction elements within each construction section, and use the construction elements as topology nodes in the corresponding line segment topology of the railway. Define the spatiotemporal dependencies between construction elements and use these dependencies as topological edges in the corresponding railway line segment topology. Once all topological nodes and edges in the railway line segment topology are defined, the topological edge paths between construction elements are associated with the railway line topology segment structure according to the execution order of the railway construction logic, thereby constructing the initial construction logic network.

2. The method for generating a railway construction simulation model based on full-line design parameters according to claim 1, characterized in that, The process of collecting track geometry parameters, geological exploration data, bridge and tunnel structural parameters, construction machinery performance indicators, and environmental constraints to construct a multi-source heterogeneous database includes: Obtain BIM files and CAD drawings for railway construction design, extract parametric design files from BIM files and CAD drawings, and obtain track geometry parameters after processing. The system integrates ground-penetrating radar detection reports, borehole exploration data, and remote sensing images for translation and interpretation. It also conducts real-time geological exploration of the railway construction area using sensors to obtain geological exploration data. The structural parameters of the bridge and tunnel were obtained by analyzing the bridge and tunnel structure using structural design software. The performance indicators of construction machinery can be obtained from the corresponding technical manuals of the construction machinery. Environmental constraints include restricted construction periods, ecological protection zones, extreme weather, and other uncontrollable factors; A data source file is constructed for each of the track geometry parameters, geological exploration data, bridge and tunnel structural parameters, construction machinery performance indicators, and environmental constraints. File indexes are assigned to these files, and all data source files are integrated into a pre-built database to construct a multi-source heterogeneous database. Each data source file creates a data temporary storage area within the multi-source heterogeneous database.

3. The method for generating a railway construction simulation model based on full-line design parameters according to claim 2, characterized in that, The process of unifying spatial coordinates and cleaning all data in a multi-source heterogeneous database to construct the design parameters for the entire line includes: Set up a first operation period to unify the spatial coordinates of all data in the multi-source heterogeneous database; set up a second operation period to clean the data of each data source file in the multi-source heterogeneous database that has completed spatial coordinate unification, and convert the data source files in each data temporary storage area in the multi-source heterogeneous database into standard data files. All standard data files are integrated to construct the full-line design parameters, which are used to characterize all line construction-related data information at each time point, each construction stage, and each construction location during railway construction.

4. The method for generating a railway construction simulation model based on full-line design parameters according to claim 3, characterized in that, The process of optimizing the construction logic network based on construction efficiency, resource scheduling rules, and dynamic constraints includes: Construct network optimization node one, network optimization node two, and network optimization node three; By analyzing whether the construction efficiency of the network optimization node affects the railway construction, if so, dynamic correction of the process schedule and optimization of the parallel pipeline are carried out; if not, no operation is performed. By analyzing the impact of resource scheduling rules on railway construction through network optimization node two, if the progress of railway construction under the current resource scheduling rules does not meet the expected progress, resource conflict resolution and resource utilization optimization will be carried out to achieve flexible resource allocation; otherwise, no operation will be performed. By embedding dynamic constraints into the construction logic network through network optimization node three, the initial construction logic network is optimized.

5. The method for generating a railway construction simulation model based on full-line design parameters according to claim 4, characterized in that, The process of defining parallel construction events in the railway construction workflow and mapping the entire line design parameters and construction logic network into a 3D visualization simulation model of railway construction through a parametric modeling engine includes: The parallel types of parallel construction events in the railway construction process are defined, and the parallel types are divided into spatial parallelism, process parallelism and resource-driven parallelism. Two construction elements with spatial adjacency in the construction logic network are respectively taken as construction events. If two construction elements belong to any parallel type, then the two construction events corresponding to the two construction elements are determined to be parallel construction events; otherwise, they are determined not to be parallel construction events. Configure the model parameters when using the parametric modeling engine to build an initial 3D railway track model. Then, use the parametric modeling engine to map all the line construction-related data information, representing each time point, each construction stage, and each construction location during railway construction, from the full line design parameters to the corresponding time segments, construction segments, and location segments pre-built in the 3D railway track model. Define and map the construction process status of each construction element included in the construction logic network, and mark different model representation colors and process progress bars for different construction process statuses. Then, a three-dimensional visualization simulation model corresponding to the current railway construction is constructed.

6. The method for generating a railway construction simulation model based on full-line design parameters according to claim 5, characterized in that, The correspondence between the construction process status and the model's displayed colors is as follows: Construction process status includes not started, in progress, and completed. When the construction process status is "not started", the model will be displayed in red. When the construction process is in progress, the model will be displayed in yellow. When the construction process is in the completed state, the model will be displayed in green. The progress range of the process progress bar is 0 to 100%. When it is 0, the construction process status is not started. When it is 100%, the construction process status is completed. When it is any other progress value, the construction process status is in progress.

7. The method for generating a railway construction simulation model based on full-line design parameters according to claim 6, characterized in that, The process of introducing real-time railway construction data into a 3D visualization simulation model to predict the probability of construction delays and determine whether to adjust construction procedures and reallocate construction resources includes: Real-time railway construction data is introduced into a 3D visualization simulation model, which then analyzes the ongoing construction section of the railway to obtain visualized construction data for the current construction section. The visualized construction data of the current construction section is processed using the Monte Carlo simulation algorithm and Bayesian prediction network to predict the probability of construction delay in railway construction. The probability of construction delay is denoted as P, and a decision threshold is set and denoted as JC. If P≥JC, then it is decided to adjust the construction procedures and reallocate construction resources. If P < JC, then no operation is performed.

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