Dike scene rapid generation method and system based on graph calculation and topological optimization

Abstract

The invention relates to the technical field of disaster emergency management and analog calculation, and relates to a dike scene rapid generation method and system based on graph calculation and topological optimization. The method comprises the following specific steps: S1, marking scene key information based on a GIS map; s2, analyzing the marked geometric data, and constructing a topological relation based on graph calculation; s3, after the topological relation is analyzed, elements needed by model calculation are extracted from the topological relation, and attributes of the elements are defined; s4, generating a rescue traffic network based on the defined element attributes and geometric information; s5, verifying the generated geometric data, the topological relation, the model elements and the traffic network; and S6, after the verification is passed, integrating all data to generate a complete simulation scene and outputting the simulation scene. According to the method, the simulation environment suitable for flood spread and breach scour calculation is rapidly constructed by marking key information of dike, breach point and simulation range scenes and combining geometric topological relation analysis and model element definition, and efficient and reliable technical support is provided for emergency response and auxiliary decision making of dike breach disasters.

Description

Technical Field

[0001] This invention relates to the field of disaster emergency management and simulation computing technology, and in particular to a method and system for rapidly generating dike scenarios based on graph computing and topology optimization. Background Technology

[0002] Floods caused by dike breaches pose a significant threat to human life and property. To effectively respond to such emergencies, rapidly constructing breach scenarios and conducting disaster simulations has become a crucial part of flood control and disaster relief decision-making. Traditional scenario construction methods typically rely on manual surveying and data collection, a cumbersome and time-consuming process that struggles to meet timely emergency needs.

[0003] In recent years, with the development of Geographic Information System (GIS) technology, scene mapping methods based on satellite imagery have been gradually applied to levee breach simulation. By marking key information such as levee location, breach point, upstream water body, and downstream disaster area on a GIS map, a simulation scene can be quickly constructed. However, how to efficiently parse this marked information, establish its topological relationships, and generate boundary conditions that meet the simulation requirements remains a pressing technical challenge.

[0004] In existing research, some scholars have used numerical simulation methods to analyze the hydraulic characteristics of dike breaches. For example, a three-dimensional numerical model based on FLOW-3D can simulate the water level field distribution of water flow at a dike breach, providing a reference for formulating closure plans. In addition, there is research on related technologies and equipment for the evolution mechanism of dike hazards and the detection of potential risks. However, these studies mainly focus on the hydrodynamic analysis after the breach, with less attention paid to the rapid construction of scenarios and the analysis of topological relationships.

[0005] In the patent field, there are already technical solutions for the rapid sealing of dike breaches. For example, a rapid dike breach sealing system based on anchor array rooting-blocking synergy employs a method of simultaneously sealing the breach from both ends of the dike. However, these patents mainly focus on emergency response after a breach, without in-depth exploration of the rapid construction of breach scenarios and the generation of simulated environments.

[0006] In summary, existing technologies still have shortcomings in the rapid construction of dike breach scenarios and the generation of simulation environments. This invention aims to rapidly construct dike breach scenarios through plotting methods, analyze their topological relationships, and generate boundary conditions and environments for simulation calculations, providing auxiliary decision support for on-site emergency response to dike breaches. Summary of the Invention

[0007] The purpose of this invention is to address the problems existing in the background technology by proposing a method and system for rapid generation of dike scenarios based on graph computation and topology optimization. By labeling key information of the scenario such as dikes, breach points, and simulation range, and combining geometric topological relationship analysis and model element definition, a simulation environment suitable for flood spread and breach scour calculation can be quickly constructed, providing efficient and reliable technical support for emergency response and auxiliary decision-making for dike breach disasters.

[0008] The technical solution of the present invention, in its first aspect, provides a method for rapidly generating dike scenes based on graph computation and topology optimization, comprising the following specific steps: S1. Key scene information is marked based on GIS map annotation; S2. Analyze the labeled geometric data and construct topological relationships based on graph calculations; S3. After the topological relationship is parsed, extract the elements needed for model calculation and define the attributes of the elements. S4. Generate a rescue transportation network based on the defined feature attributes and geometric information; S5. Verify the generated geometric data, topological relationships, model elements, and traffic network; S6. After verification, integrate all data to generate a complete simulation scenario and output a standardized data file for use by simulation software.

[0009] Preferably, in step S1, the location of the dike, the breach point, the simulated range, the upstream water body and the downstream disaster area in the dike breach scenario are marked on the GIS map in the form of points, polylines, rectangles or polygons.

[0010] Preferably, in step S1, the dike is marked in the form of a polyline to clearly indicate its starting point, ending point and direction; Breach points are marked as dots to indicate the location of the breach and related information; The entire spatial range of the simulation calculation is represented by rectangles or polygons to ensure clear scene boundaries; The upstream water body and the downstream disaster area are marked with preset geometric shapes; this step provides the basic geometric information for scene construction and lays the data foundation for subsequent topology analysis.

[0011] Preferably, in step S2, the labeled geometric data is parsed to calculate the topological relationships therein; First, all points, lines, and surfaces are analyzed one by one, and the intersection points of polylines and line segments in polygons are calculated. Based on the line segment intersection points, the entire scene is divided into multiple closed polygonal regions. Finally, the connection relationship between labeled objects is established through graph structure to clarify the topological association. This step generates a clear topological graph through geometric calculation, providing an accurate structural basis for subsequent element selection and attribute definition.

[0012] Preferably, the elements in step S3 include the dike segment, the breach point, the upstream area, and the downstream area; These elements are defined sequentially, including the material, top width, and location of the dike, the initial width and dynamic attributes of the breach point, as well as the input conditions of the upstream water body and the extent of the downstream disaster area. This step, through precise element selection and attribute definition, provides comprehensive physical and environmental parameter support for model calculation.

[0013] Preferably, the rescue traffic network generated in step S4 extends to both sides of the embankment section as the center line to generate two-way lanes, and sets the lane width and traffic rules to ensure that the simulated traffic network is consistent with the actual rescue needs; at the same time, the generated traffic network is connected with the existing road network in the GIS map to form a complete passage route for rescue vehicles; this step provides traffic support for disaster relief and is an important link in decision support.

[0014] Preferably, in step S5, the verification content includes whether the annotation is complete, whether the geometric topology analysis is correct, whether the model element attribute definition meets the simulation requirements, and whether the rescue transportation network is connected normally. If a problem is found, the user is prompted to return to the annotation step to supplement or adjust the annotation information to ensure that the final scene meets the calculation requirements.

[0015] Preferably, in step S6, the generated scenario includes the boundary conditions for flood spread calculation, the initial parameters for breach scour simulation, and traffic network information related to rescue, and is output in the form of a data file for direct use by disaster simulation software; through this step, the system achieves the ultimate goal of scenario construction, providing comprehensive and efficient decision support for emergency response to dike breach disasters.

[0016] A second aspect of the present invention provides a rapid generation system for dike scenes based on graph computation and topology optimization, which rapidly generates dike scenes according to the above method, including: Annotation module: Used to annotate key scene information on GIS maps; Topology parsing module: used to parse geometric data and generate topological relationships; Feature definition module: used to extract model features and define attributes; Road network generation module: used to generate emergency transportation networks; Verification module: Used to verify the completeness and correctness of the scene construction; Scene generation module: Used to integrate all data and output simulated scene files.

[0017] Preferably, the topology analysis module uses graph computation to calculate the intersection points of line segments and closed regions.

[0018] Preferably, the road network generation module supports automatic connection to the GIS road network and generates lane data with traffic attributes.

[0019] A third aspect of the present invention provides a computer program product comprising a computer program that, when executed by a processor, implements the steps of the method described above.

[0020] Compared with the prior art, the present invention has the following beneficial technical effects: 1. This invention deeply integrates GIS annotation data with topological relationship calculation. By parsing user-annotated point, line, and polygon data, it automatically identifies spatial relationships between geometric objects, such as line segment intersections, adjacent regions, and closed polygons. Based on the topological analysis results, the system can dynamically generate precise divisions of the simulation area and key regions such as upstream and downstream, meeting the needs of diverse simulation scenarios. This method breaks through the limitations of traditional static region definitions, eliminating the need for manually inputting fixed boundary conditions, and instead achieving flexible region division through automatic calculation. Especially in complex scenarios (such as multiple breaches or multiple levees in parallel), this technology significantly improves the efficiency and accuracy of scene construction, providing more accurate and reliable boundary conditions for simulation calculations.

[0021] 2. This invention, based on the geometric characteristics of levee segments, employs normal vector expansion calculation technology to generate high-precision bidirectional rescue lanes. These lanes are precisely deployed according to the top width of the levee, ensuring compatibility between the levee's own geometric characteristics and the traffic network. Simultaneously, the system automatically identifies the levee's starting and ending points and efficiently connects the rescue lanes to the existing GIS road network using a shortest path algorithm, achieving comprehensive connectivity of the rescue network. This innovative method solves the problems of excessive manual intervention and low connection efficiency in traditional rescue traffic planning, significantly improving the convenience and reliability of rescue resource allocation. In emergency rescue scenarios, this function supports the rapid and seamless generation of vehicle traffic networks, providing crucial support for the smooth operation of rescue work.

[0022] 3. This invention introduces graph computing technology to construct a topological relationship graph for point, line, and surface geometric objects in a scene. By analyzing the connectivity, containment, and adjacency relationships of spatial objects, it achieves efficient generation of the regions and networks required for simulation calculations. This method significantly improves the processing capability of complex geometric scenes, enabling rapid handling of highly complex problems such as intersecting line segments and multi-region partitioning. Compared to traditional geometric calculation methods, graph computing has higher efficiency and scalability, not only adapting to diverse levee breach scenarios but also maintaining computational stability and accuracy when dynamic adjustments are required. This technology provides optimized analytical tools for scene construction, ensuring the flexibility and data accuracy of the simulation process. Attached Figure Description

[0023] Figure 1This is a flowchart of the rapid generation method in an embodiment of the present invention; Figure 2 This is a schematic diagram of the line segment marking in an embodiment of the present invention; Figure 3 This is a schematic diagram of the breach segment labeling in an embodiment of the present invention; Figure 4 This is a schematic diagram of the simulated range marking in an embodiment of the present invention; Figure 5 This is a comparison diagram of the effects of existing technical solutions and the solution in this application. Detailed Implementation

[0024] Example 1 This embodiment proposes a method for rapidly generating dike scenarios based on graph computation and topology optimization, which includes the following steps: S1. Key scene information is marked based on GIS map annotation; S2. Analyze the labeled geometric data and construct topological relationships based on graph calculations; S3. After the topological relationship is parsed, extract the elements needed for model calculation and define the attributes of the elements. S4. Generate a rescue transportation network based on the defined feature attributes and geometric information; S5. Verify the generated geometric data, topological relationships, model elements, and traffic network; S6. After verification, integrate all data to generate a complete simulation scenario and output a standardized data file for use by simulation software.

[0025] To further understand this solution, a specific case will be used below to explain each step of the method in detail.

[0026] S1. GIS-based annotation of key scene information Step S1 is the starting point of the entire invention, aiming to visualize and annotate key information in a dike breach scenario using a GIS map, providing a geometric foundation for subsequent topological calculations and simulation generation. In this process, users annotate dikes, breach points, simulation ranges, and related upstream and downstream area information on the GIS map interface based on actual needs. The annotated data is stored in standardized point, polyline, rectangle, or polygon format to ensure that topological relationships can be calculated through geometric analysis.

[0027] (1) Dike marking The dike is the core information of the scene, marked using polylines. Users specify the start and end points of the dike on the map, and also mark its direction and key control points. After marking, the system stores the dike as a set of polyline data in a two-dimensional coordinate array format; the marked diagram is shown below. Figure 2 As shown.

[0028] (2) Marking of the breach section Breach segment marking is used to determine the potential location and initial conditions of dike failure. Users mark breach segments on dike lines and record relevant information, such as breach width. Breach segments are stored as line segment features with attributes, and their marked illustrations are shown below. Figure 3 As shown.

[0029] (3) Simulation range labeling The simulation extent is used to define the spatial boundaries of the calculation and can be labeled with rectangles or polygons. Users mark the area covered by the scene by drawing rectangles or polygons on the map. The simulation extent is stored as polygonal features, and its labeled illustration is shown below. Figure 4 As shown.

[0030] The key information obtained through GIS annotation provides the geometric foundation and environmental conditions for subsequent steps such as topology analysis and model feature definition. The annotated data is stored in a standardized format, facilitating parsing and use in subsequent processing and ensuring the consistency and accuracy of the entire process.

[0031] S2, Topological relation generation in set data parsing and graph computation; Analyzing geometric data and calculating topological relationships is a key step in the invention. Its purpose is to perform geometric analysis on the point, line, and polygon data marked by the user on a GIS map, identifying the topological relationships between marked objects, such as intersections of line segments and closed regions. Through this process, a basic topological structure suitable for simulation calculations is generated, laying the foundation for the definition and selection of model elements.

[0032] (1) Calculation of the intersection of line segments First, analyze all line segments in the annotations and identify the intersections between them. In particular, accurately calculate the intersection points and segment the geometry where dike segments, polygon boundary segments, and different annotated objects intersect. Calculating the intersection points between all annotated line segments and identifying and processing their intersection relationships lays the foundation for subsequent topology construction.

[0033] Input data: User-annotated points, polylines, rectangles, or polygons.

[0034] Calculation steps: Input data preparation: Retrieve all line segment data marked by the user on the GIS map and store them as a set. .

[0035] Each line segment is represented as a pair of coordinates of its two endpoints, in the form of: ,in , .

[0036] Pairwise line segment detection: For sets Each pair of line segments Perform an intersection test.

[0037] Intersection determination: Use vector cross product or bounding box method for preliminary judgment to reduce the amount of calculation.

[0038] Quick Exclusion Method: If the circumscribed rectangles of two line segments do not overlap, then the line segments do not intersect.

[0039] Straddle Test: Given a line segment... The endpoints are , line segment The endpoints are , .

[0040] calculate: if and If the line segments intersect, then they will intersect.

[0041] Calculate the coordinates of the intersection point: If line segments intersect, use parametric equations to calculate the intersection point. .

[0042] Let line segment Parametric equations: line segment Parametric equations: Solve the system of equations: Calculate the parameters , Substitute the values ​​to obtain the coordinates of the intersection point. .

[0043] Line segment division: Intersecting line segments are divided into two new line segments at the intersection point.

[0044] Update line segment set Replace the original line segment.

[0045] Output the intersection points and the updated set of line segments: Store all intersections in a set middle.

[0046] Updated set of line segments It includes all non-intersecting line segments.

[0047] Data structure design: Point: Point(x: number, y: number) Line: Line(points: Point[]) pseudocode: Iterate through all pairs of lines in pairs, and let the current pair be (a, b). Iterate through all segments on lines a and b, and let the current segment pair be (c, d). If line segments c and d intersect, take the intersection point e. Divide line segments c and d based on point e. If the division is successful, insert point e into either line segment c or line segment d. Output data: Updated line segment and intersection data.

[0048] (2) Generation of closed regions After calculating the intersection points, closed geometric regions (i.e., polygons) are generated using the connectivity of all line segments. These closed regions can be direct results of user annotations or new regions generated by topological calculations.

[0049] Generation steps: 1. Construct the topology graph: Construct an undirected graph G by treating all points (including endpoints and intersections) as nodes and line segments as edges.

[0050] 2. Loop detection: Search for all simple cycles (closed paths) in graph G. Algorithm choice: Use Tarjan's algorithm or Johnson's algorithm to find all simple cycles.

[0051] 3. Generate polygons: Transform the node sequence corresponding to each simple ring into a vertex sequence of a polygon.

[0052] 4. Polygon validity check: Check if the polygon is a simple polygon (edges do not intersect).

[0053] Calculate the area of ​​polygons and filter out polygons that are too small or too large.

[0054] 5. Assigning region attributes: Based on the location and relationships of the polygon, it can be determined whether it is an upstream water body, a downstream disaster area, or another area.

[0055] Data structure design: Edge: Edge(start: Point, end: Point) Graph: Graph(vertices: Point[], edges: Edge[]) pseudocode: Data preprocessing: Flatten all points on the line segments and remove duplicates. Each unique point is assigned a unique ID (using the string form of the point's coordinates). Constructing an undirected graph: Create an undirected graph Treat all unique points as nodes in the graph. Treat all line segments as edges of the graph (connecting adjacent points). Find all cycles (closed paths): Perform a depth-first search (DFS) on each node. When DFS encounters the starting point and the path length is greater than 2, a cycle is found. Record the path and sorted node IDs for each ring. Remove duplicate cycles (by comparing sorted node IDs). Transform the ring into a polygon: Convert each found ring into a polygon. Add a starting point at the end of each loop to close the polygon. Filter out polymorphs that do not contain each other and return the data; Output data: Closed polygon data generated by topology calculation.

[0056] (3) Construction of topological relationship graph Based on the generated point, line, and polygon data, a topology diagram is constructed. The topology diagram is used to represent the spatial relationships between objects, such as adjacency, containment, and intersection, which facilitates the subsequent selection of model elements.

[0057] Implementation steps: 1. Construct the adjacency matrix: Given an undirected graph G, construct the adjacency matrix between nodes.

[0058] 2. Calculate inclusion relationships: Use algorithms that determine if a point is inside a polygon (such as the ray method) to determine the inclusion relationship between a point and a region.

[0059] 3. Storage topology: Create a topological relationship table to record the spatial relationships between various geometric objects.

[0060] Data structure design: TopologyRelation class: class TopologyRelation: def __init__(self): self.adjacency_matrix = {} self.contains = {} self.intersects = {} By parsing geometric data and calculating topological relationships, the system extracts intersections and generates closed regions from the user-annotated basic geometric information, and establishes a topological relationship graph, providing an accurate structural foundation for subsequent model element selection and attribute definition. This step combines geometric calculation and topological analysis, greatly improving the processing efficiency and completeness of scene data.

[0061] S3. Model element extraction and definition based on topology structure After completing the geometric data parsing and topological relationship calculations, the next step is to select model elements and define attributes. The purpose of this step is to extract core elements (such as dikes and breach points) from the generated geometric and topological data for simulation calculations, and to assign necessary physical and environmental attributes to each element to meet the needs of model calculations.

[0062] (1) Select model elements The system identifies and filters out core elements that meet the simulation requirements from the geometric data obtained by topological analysis. These elements include, but are not limited to: Embankment segments: Extracted from the marked embankment polyline and further divided into independent segments.

[0063] Breach point: Extracted from user-annotated points and located relative to the dike using topological data.

[0064] Upstream and downstream areas: From the closed polygons generated by the topology, the user manually selects appropriate areas to define the upstream water body and the downstream flood spread area, respectively.

[0065] Elements extracted from the analysis results (2) Define physical properties Assign physical and environmental attributes to the extracted core elements to meet the needs of subsequent model calculations: Embankment Section: Attributes: Material (concrete, soil, etc.), top width, bottom width, height, etc.

[0066] Breach point: Attributes: breach width, initial water flow, maximum expansion width, etc.

[0067] Upstream water body and downstream area: Attributes: water level elevation, area, flow rate, boundary type (closed or open), etc.

[0068] (3) Data storage and structure optimization The model elements and their attributes defined above are stored in a standardized format for easy retrieval in subsequent simulation calculations. The data format uses GeoJSON or other compatible formats to support different simulation platforms and tools.

[0069] Optimization points: Indexing mechanisms accelerate feature retrieval.

[0070] Structured storage of topological relationships facilitates quick retrieval of adjacent elements.

[0071] By selecting model elements and defining attributes, the geometric topology analysis results are transformed into input data that meets simulation requirements. Flexible definition of element attributes supports various simulation scenarios, effectively improving the practicality and accuracy of scenario generation. This step lays a solid foundation for subsequent generation and verification of the rescue road network.

[0072] S4. Topology Optimization and Generation of Rescue Transportation Network This step automatically generates a traffic network for rescue vehicles based on the geometric information of the levee segments. The generation of the rescue network comprehensively considers the geometric features of the levee (such as top width and orientation) and the connectivity of the existing GIS road network to ensure the formation of a passable and operable rescue transportation system. The following content provides a detailed explanation of the specific algorithm and implementation details, and uses pseudocode to aid in understanding the key logic.

[0073] (1) Generate two-way lanes based on embankment segments The system uses the embankment segment as the centerline and expands to both sides according to the embankment's top width to generate two-way lanes. The expansion process is based on the embankment's direction vector to ensure that the lane width is evenly distributed on both sides of the embankment.

[0074] Core steps: 1. Calculate the direction vector of the embankment segment.

[0075] 2. Calculate the offset coordinates of the left and right lanes based on the direction vector and top width.

[0076] 3. Generate the geometric data for the two-way lanes.

[0077] (2) Connection with GIS road network To ensure the generated emergency transportation network integrates into the overall transportation system, the system connects both ends of the lanes to existing road network nodes in the GIS map. This connection process includes: Find the nearest GIS road network nodes near the starting and ending points of the dike.

[0078] Connecting line segments are generated based on the shortest path algorithm to ensure road network connectivity.

[0079] (3) Generate a complete transportation network A complete emergency transportation network is generated by combining two-way lanes and GIS connecting segments. Each component of the transportation network (lanes and connecting segments) is assigned relevant attributes, such as direction of travel, maximum carrying capacity, and priority.

[0080] Core steps: 1. Merge two-way lanes and connecting road segments into a unified traffic network data.

[0081] 2. Assign attribute information to each line segment, for example: Traffic direction (two-way or one-way).

[0082] Maximum load capacity (e.g., 30 tons).

[0083] Urgency priority (e.g., high, low).

[0084] Using the algorithm described above, the system realizes the entire process of generating two-way lanes from embankment segments and connecting them to the GIS road network to construct a complete rescue transportation network. Key pseudocode demonstrates the core logic of expanding lanes, connecting GIS nodes, and integrating the transportation network. The generated transportation network not only possesses accurate geometric features but also contains detailed attribute information, providing reliable basic data for subsequent emergency dispatching and decision support.

[0085] S5. Verification and Dynamic Adjustment of Scene Generation Results After generating the rescue traffic network, to ensure the integrity and correctness of the entire scene construction process, the system verifies all generated geometric data, topological relationships, model elements, and traffic networks. This verification step checks whether the scene meets the requirements of the simulation calculation and prompts the user to supplement or correct any parts that do not meet the conditions. Once the verification is successful, the system proceeds to the final scene generation stage.

[0086] (1) Verification content The verification process covers the following main aspects: 1. Geometric integrity verification Check whether the points, lines, and surfaces marked by the user form closed geometric structures, and whether there are isolated points or unclosed line segments. For example: all line segments must be correctly segmented; whether the marked dike segments and breach point locations match.

[0087] 2. Topology Consistency Verification Verify that the generated topology diagram accurately reflects the spatial relationships between geometric objects. For example, check if the intersection points of intersecting line segments are generated correctly; and whether the divided regions contain all the information annotated by the user.

[0088] 3. Model element validation Ensure that the attributes defined for model elements are complete and meet the simulation requirements. For example, are the parameters such as the top width and material of the dike complete? Do the initial width and location of the breach point match the scene settings?

[0089] 4. Rescue transportation network verification Check whether the generated traffic network is connected and correctly linked to the GIS road network. For example: whether the expansion of the embankment lanes matches the top width; whether the connecting segments reach the nearest GIS node.

[0090] (2) Verification method The verification method uses automated algorithms to check the integrity and consistency of the scene data item by item.

[0091] (3) Feedback of verification results Based on the verification results, the system will generate a feedback report, including: The "Pass" section indicates the geometric structures, topological relationships, and attribute definitions that have met the conditions.

[0092] Unaccepted sections: Specify in detail the content that needs to be corrected or supplemented. For example: a marked line segment does not form a closed area; the attributes of the breach point are incomplete; the rescue transportation network has isolated segments that are not connected to the GIS road network.

[0093] (4) Scene supplementation and correction If the validation fails, the system will guide the user back to the relevant step (such as GIS annotation, model feature definition, or traffic network generation) to supplement or correct any incomplete or incorrect parts. After the user makes the corrections, the validation will be re-executed until it passes.

[0094] Verifying the scenario construction results is a crucial step in ensuring the reliability and integrity of the simulated scenario. This step uses automated verification algorithms to validate the geometry, topology, attributes, and network item by item, providing clear feedback reports to help users quickly locate and correct problems. After successful verification, the final rapid scenario generation stage begins.

[0095] S6. Quickly generate complete simulation scenes After verification, the system integrates all labeled data, topology analysis results, model element definitions, and rescue transportation networks to quickly generate a complete simulation scenario. This scenario includes all the geometric boundary conditions, physical parameters, and dynamic configuration files required for calculation, and is output in a unified format for direct use by disaster simulation software. This step is the endpoint of the entire scenario construction process and the starting point for decision support.

[0096] (1) Data integration The system integrates the following content into a simulation scenario: 1. Geometric data: including dike segments, breach points, simulated boundaries, and upstream and downstream areas.

[0097] 2. Topological relationships: The generated segmented regions and their adjacent relationships.

[0098] 3. Model elements: All fully defined physical properties (such as levee width, initial breach conditions, upstream water flow, etc.).

[0099] 4. Rescue Traffic Network: The generated rescue lanes and their connection information with the GIS road network.

[0100] The integration process ensures data consistency and organizes all parts of the content in a unified structure.

[0101] (2) Output simulation scene file The integrated scenario data is exported in a standardized format for easy integration with disaster simulation systems. Common output formats include: GeoJSON: Used to represent geometric and attribute data.

[0102] Model-specific formats: such as input files for specific disaster simulation software (e.g., ASCII grid, HDF5, etc.).

[0103] (3) Automated generation logic Scene generation employs automated logic to ensure the completeness and consistency of the output. The following are the main steps in generating a scene: 1. Integrate geometric and topological data to create a unified spatial reference.

[0104] 2. Organize the model elements and their attributes, and populate them into the corresponding data structures.

[0105] 3. Verify the completeness of the scenario to ensure that no elements required for the calculation are missing.

[0106] 4. Export standardized files and provide scene preview functionality.

[0107] (4) Provide scene preview To facilitate user confirmation of the generated results, the system supports a scene visualization preview function. The preview content includes: geometric display of dikes, breach points, and transportation networks; interactive query of attribute information; and graphical display of scene boundaries and topological relationships.

[0108] By rapidly generating simulation scenarios, the system integrates complete geometric, topological, and attribute data, providing accurate and standardized input conditions for disaster simulation models. The output scenario files can be used directly for simulation calculations, or the visual preview function can assist users in further verifying and optimizing the scenario content. The efficiency and accuracy of this step ensure the final effectiveness of the dike breach scenario construction, providing strong support for emergency response.

[0109] To further verify the effectiveness of this application, please refer to... Figure 5 A comparison between the traditional solution and the solution of this application shows that: Combining the visualized path morphology and performance data above, we can clearly see the fundamental differences between the two technical approaches. The geometric approach on the left simulates the behavior of a traditional GIS / CAD system, where the path strictly passes through the midpoints of the grid edges. This requires the CPU to perform a large number of floating-point operations (point-in-polygon, ray casting) in real time, resulting in high computation time, which increases exponentially with the complexity of the scene.

[0110] In contrast, the solution proposed in this application is as follows: Figure 5 The topology graph on the right exhibits a completely different characteristic. The paths are presented as center homing connections of polygon centroids because we have discretized the continuous space into a "graph" through preprocessing. At runtime, the algorithm no longer cares about the geometry, only requiring extremely fast pointer jumps in memory.

[0111] Test data shows that the topology solution achieves a two-order-of-magnitude performance improvement by sacrificing negligible geometric smoothness. This "space-for-time" strategy perfectly meets the timeliness requirements of "real-time simulation of massive intelligent agents" in dike flood control scenarios, verifying the advanced nature and engineering practical value of the patented technology solution.

[0112] This invention significantly improves the efficiency and accuracy of constructing dike breach scenarios by introducing graph computation and topology optimization techniques. Compared to traditional manual surveying and data collection methods, this invention enables rapid annotation and automatic parsing of key scenario information, greatly shortening the scenario construction cycle and saving valuable time for emergency response. Simultaneously, by constructing precise topological relationships, this invention ensures the accuracy and reliability of simulated boundary conditions, providing solid data support for flood spread and breach scour simulation. Furthermore, this invention supports the automatic generation and verification of rescue transportation networks, providing efficient transportation support for disaster relief and further enhancing the scientific rigor and precision of flood control and disaster relief decision-making. In summary, this invention demonstrates significant advantages in the rapid construction of dike breach scenarios and the generation of simulated environments, possessing broad application prospects and promotional value.

[0113] Example 2 This embodiment provides a rapid embankment scene generation system based on graph computation and topology optimization. It rapidly generates embankment scenes according to the method in Embodiment 1, including: Annotation module: Used to annotate key scene information on GIS maps; Topology parsing module: used to parse geometric data and generate topological relationships; Feature definition module: used to extract model features and define attributes; Road network generation module: used to generate emergency transportation networks; Verification module: Used to verify the completeness and correctness of the scene construction; Scene generation module: Used to integrate all data and output simulated scene files.

[0114] In this embodiment, the topology analysis module uses graph computation to calculate the intersection points of line segments and closed regions.

[0115] In this embodiment, the road network generation module supports automatic connection to the GIS road network and generates lane data with traffic attributes.

[0116] This system is fully automated and highly accurate, from the input of annotation information to the output of the final simulation scenario file. The annotation module allows users to intuitively annotate key information such as dikes and breach points on a GIS map, providing foundational data for subsequent processing. The topology analysis module uses graph computing technology to quickly analyze geometric data and generate accurate topological relationship diagrams, laying a solid foundation for feature definition and road network generation. The feature definition module intelligently extracts core features from the topology data and assigns them rich physical and environmental attributes to meet the needs of different simulation scenarios. The road network generation module automatically generates a well-connected rescue transportation network based on the geometric characteristics of the dikes and GIS road network information, ensuring that rescue vehicles can quickly reach designated locations. The verification module rigorously verifies all generated data to ensure the integrity and correctness of the scenario construction. Finally, the scenario generation module integrates all data into a standardized simulation scenario file for direct use by disaster simulation software. The entire system workflow is tightly integrated, with each module working collaboratively, greatly improving the efficiency and quality of dike scenario generation.

[0117] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A method for rapidly generating dike scenes based on graph computation and topology optimization, characterized in that, The specific steps include the following: S1. Key scene information is marked based on GIS map annotation; S2. Analyze the labeled geometric data and construct topological relationships based on graph calculations; S3. After the topological relationship is parsed, extract the elements needed for model calculation and define the attributes of the elements. S4. Generate a rescue transportation network based on the defined feature attributes and geometric information; S5. Verify the generated geometric data, topological relationships, model elements, and traffic network; S6. After verification, integrate all data to generate a complete simulation scenario and output a standardized data file for use by simulation software.

2. The method for rapid generation of dike scenes based on graph computation and topology optimization according to claim 1, characterized in that, In step S1, the location of the dike, the breach point, the simulation range, the upstream water body and the downstream disaster area in the dike breach scenario are marked on the GIS map in the form of points, polylines, rectangles or polygons.

3. The method for rapid generation of dike scenes based on graph computation and topology optimization according to claim 2, characterized in that, In step S1, the dike is marked with a polyline to clearly indicate its starting point, ending point, and direction; Breach points are marked as dots to indicate the location of the breach and related information; The entire spatial range of the simulation calculation is represented by rectangles or polygons to ensure clear scene boundaries; The upstream water body and the downstream disaster area are marked using preset geometric shapes.

4. The method for rapid generation of dike scenes based on graph computation and topology optimization according to claim 1, characterized in that, In step S2, the labeled geometric data is parsed, and the topological relationships are calculated. First, analyze all points, lines, and surfaces one by one, and calculate the intersection points of polylines and line segments in polygons; divide the entire scene into multiple closed polygonal regions based on the line segment intersection points; finally, establish the connection relationship between labeled objects through graph structure to clarify the topological association.

5. The method for rapid generation of dike scenes based on graph computation and topology optimization according to claim 1, characterized in that, The elements in step S3 include the dike segment, the breach point, the upstream area, and the downstream area; These elements are defined sequentially, including the material, top width, and location of the dike, the initial width and dynamic attributes of the breach point, as well as the input conditions of the upstream water body and the extent of the downstream disaster area.

6. The method for rapid generation of dike scenes based on graph computation and topology optimization according to claim 1, characterized in that, The rescue traffic network generated in step S4 extends to both sides of the embankment section as the center line to generate two-way lanes. The lane width and traffic rules are set to ensure that the simulated traffic network is consistent with the actual rescue needs. At the same time, the generated traffic network is connected with the existing road network in the GIS map to form a complete passage route for rescue vehicles.

7. The method for rapid generation of dike scenes based on graph computation and topology optimization according to claim 1, characterized in that, In step S5, the verification content includes whether the annotation is complete, whether the geometric topology analysis is correct, whether the model element attribute definition meets the simulation requirements, and whether the rescue transportation network is connected normally. If a problem is found, the user is prompted to return to the annotation step to supplement or adjust the annotation information to ensure that the final scenario meets the calculation requirements.

8. The method for rapid generation of dike scenes based on graph computation and topology optimization according to claim 1, characterized in that, In step S6, the generated scenario includes the boundary conditions for flood spread calculation, the initial parameters for breach scour simulation, and traffic network information related to rescue, and is output in the form of a data file for direct use by disaster simulation software.

9. A rapid generation system for dike scenes based on graph computation and topology optimization, wherein the method described in any one of claims 1-8 rapidly generates dike scenes, characterized in that, include: Annotation module: Used to annotate key scene information on GIS maps; Topology parsing module: used to parse geometric data and generate topological relationships; Feature definition module: used to extract model features and define attributes; Road network generation module: used to generate emergency transportation networks; Verification module: Used to verify the completeness and correctness of the scene construction; Scene generation module: Used to integrate all data and output simulated scene files.

10. The rapid generation system for dike scenes based on graph computation and topology optimization according to claim 9, characterized in that, The topology analysis module uses graph calculation to calculate the intersection points of line segments and closed regions; the road network generation module supports automatic connection to the GIS road network and generates lane data with traffic attributes.

Images