Path analysis and risk identification method and system for water infiltration outside cavern group of hydropower station

Abstract

According to the hydropower station cavern group external water infiltration path analysis and risk identification method and system provided by the invention, the water catchment network model of the underground cavern group is established, the propagation path of the water flow is dynamically simulated, the external water infiltration risk is comprehensively evaluated, and the water flow path is displayed; and comprehensive external water infiltration path analysis and risk identification of the complex underground cavern group are realized. The method effectively solves the problems that the accuracy of the risk assessment result of water inflow and seepage of the cavern group of the hydropower station is low, and the propagation path and the sweep range of the water flow are difficult to accurately predict, and provides a scientific water flow management and protection scheme for the hydropower station. Scientific technical support is provided for anti-seepage design, risk management and emergency response of the underground powerhouse of the hydropower station, and the method has high engineering practical significance.

Description

Technical Field

[0001] The invention belongs to the technical field of water conservancy projects and relates to a path analysis and risk identification method and system for external water infiltration. Background Art

[0002] The underground powerhouse caverns of hydropower stations are greatly affected by complex geological conditions and hydrological environment. They are characterized by deep burial, high-pressure water environment and complex channel connection network. The problem of external water infiltration poses a major threat to their safety. Underground caverns are often located in catchment areas or areas with abundant groundwater. Water flows into the underground powerhouses of hydropower stations through surface rainfall, groundwater infiltration and other channels, which may cause structural damage, facility failure, emergency shutdown, etc. of the underground powerhouses of hydropower stations, and even lead to major production safety accidents. Therefore, in order to ensure the safe and stable operation of large-scale hydropower projects, it is very necessary to conduct risk assessment of external water infiltration and flow path analysis of the caverns of hydropower stations.

[0003] At present, the risk assessment of water inflow and infiltration in hydropower station caverns mainly relies on experience judgment and simple hydrological analysis, lacks systematic automatic analysis tools, and is often based on qualitative judgment or local data. There is a lack of comprehensive understanding of the water collection channels of the entire cavern group, especially when facing complex geological conditions, and the accuracy of risk assessment results is low. The current water flow monitoring technology of hydropower station caverns mainly relies on fixed-point monitoring equipment, such as seepage monitors and water pressure sensors. These devices can only provide local monitoring data, and cannot intuitively show how water flow spreads from a certain node to other nodes and lines in a complex and changeable underground environment. It cannot fully display the water flow path and water flow propagation area, and it is difficult to accurately predict the water flow propagation path and its range, and it is impossible to provide managers with comprehensive and dynamic risk analysis and emergency plans. Summary of the invention

[0004] In order to solve the problems in the background technology of low accuracy of risk assessment results of water infiltration in hydropower station cavern groups and difficulty in accurately predicting the propagation path of water flow and its affected range, the present invention provides a path analysis and risk identification method and system for water infiltration outside hydropower station cavern groups.

[0005] The method of the present invention comprises:

[0006] According to the structure and connectivity data of the hydropower station caverns, nodes are used to represent the intersections of caverns or channels, and connected lines are used to represent the underground caverns or channels connecting the nodes, so as to construct a cavern group water catchment network model.

[0007] Based on the areas where surface water is concentrated or the areas around the caverns that are prone to external water infiltration, select the potential risk points of external water infiltration in the cavern catchment network model, and input the external water infiltration related parameters including rainfall, groundwater level and water flow penetration for each potential risk point;

[0008] According to the potential risk points of external water infiltration and the parameters related to the external water infiltration at each potential risk point, the propagation path of external water infiltration is analyzed using the hydraulic flow dynamics simulation algorithm to simulate the propagation process of water flow in the connected network of underground caverns.

[0009] According to the propagation process of water flow in the connected network of underground caverns, the length of the water flow path, the coverage area of ​​the water flow and the elevation difference of the water flow spread are obtained. The shortest path from the water flow input node to the target node, the maximum spread range of the water flow and the water flow elevation change diagram are calculated to realize the path analysis of the external water infiltration of the hydropower station cavern group;

[0010] Based on the length of the water flow path, the coverage area of ​​the water flow, and the elevation difference of the water flow, a risk assessment is conducted on each node and connecting line of the cavern group water collection network model to identify the risk of external water infiltration into the hydropower station cavern group.

[0011] Furthermore, in the cavern group water collection network model, the attributes of the nodes include: node location, node elevation, node type, and permeability; the node types include caverns, water collection points, and intersection points;

[0012] In the cavern group water catchment network model, the attributes of the connected lines include: line length, slope, undulation, channel cross-sectional dimensions, material properties, and permeability;

[0013] In the construction of the cavern group water collection network model, based on the topographic data, geological conditions, fault distribution and groundwater data of the hydropower station cavern group, according to the hydrodynamics and geological engineering theory, the movement law of water flow in the complex geological structure is described by the fluid dynamics equation between the nodes and the lines, and the connectivity logic diagram of the hydropower station cavern group is generated, which is used as the connectivity relationship data of the hydropower station cavern group.

[0014] Furthermore, among the parameters related to external water infiltration, rainfall is obtained through historical rainfall data or real-time meteorological data, groundwater level is the groundwater level affecting infiltration obtained based on groundwater data, and water flow infiltration is set by regional permeability test results and material properties.

[0015] Furthermore, the method for simulating the propagation process of the water flow in the connected network of the underground cavern group includes:

[0016] Conduct initial water flow distribution simulation: Starting from the selected potential risk points for external water infiltration, simulate how water flows into the underground cavern network and how water flows propagate between nodes and lines based on the influence of gravity, permeability and geological resistance;

[0017] Conduct path propagation analysis: Based on the elevation difference between nodes, the undulation and slope of the line, the water flow preferentially flows to the nodes with lower elevations, determine the flow direction and path of the water flow, and obtain the flow velocity and range of the water flow in each line according to the channel capacity of different lines;

[0018] Perform extended path calculation: The path of water flow starting from the infiltration point, passing through each line and reaching other nodes is calculated through repeated iterations. During the process of water flow spreading, the water flow transmission capacity of each line is calculated to evaluate the farthest range that the water flow may reach.

[0019] Furthermore, in the path analysis of external water infiltration in the hydropower station cavern group, the shortest path is the shortest propagation path from the water flow input node to the target node; the maximum spread range is the maximum range in which the water flow can propagate, that is, the farthest node and connecting line that the water flow may reach; the elevation change map is an elevation change map of the water flow along the way obtained based on the distribution of the water flow at different elevations.

[0020] Furthermore, in the path analysis of water infiltration from outside the hydropower station cavern group, based on the propagation process of water flow in the connected network of the underground cavern group, the starting point of the water flow, the nodes and lines through which the water flow passes, and the nodes and connected lines affected by the water flow are marked with different colors to show the process of water flow spread and the expansion path and speed of the water flow.

[0021] Furthermore, in the risk identification of water infiltration outside the hydropower station cavern group, the calculation formula for risk assessment is:

[0022] R=α×L+β×A+γ×H,

[0023] In the formula, R is the risk value of each node; L is the length of the water flow path; A is the coverage area of ​​the water flow; H is the elevation difference of the water flow spread; α, β, and γ are all weight coefficients of risk assessment, which are set according to specific engineering experience;

[0024] The risk value of the node is compared with the set threshold, and the node is divided into a low-risk area, a medium-risk area and a high-risk area; the setting of the threshold can be optimized based on historical data analysis, simulation result calibration and dynamic adjustment of the actual environment.

[0025] To implement the above-mentioned method, the present invention also proposes a path analysis and risk identification system for external water infiltration into a hydropower station cavern group, including a cavern group water collection network model construction module, a potential risk point selection module, an external water infiltration spread path simulation module, an external water infiltration path analysis module, and an external water infiltration risk identification module.

[0026] The cavern group water collection network model construction module is used to construct a cavern group water collection network model based on the structure and connectivity relationship data of the hydropower station cavern group, with nodes representing the intersection points of each cavern or channel, and with connecting lines representing the underground caverns or channels connecting each node.

[0027] The potential risk point selection module is used to select potential risk points of external water infiltration in the cavern group water collection network model based on places where surface water is concentrated or areas around the cavern group where external water infiltration is prone to occur, and input external water infiltration related parameters including rainfall, groundwater level and water flow penetration for each potential risk point.

[0028] The external water infiltration spreading path simulation module is used to analyze the spreading path of external water infiltration using a hydrodynamic simulation algorithm based on potential risk points of external water infiltration and external water infiltration volume-related parameters of each potential risk point, and simulate the propagation process of water flow in the connected network of the underground cavern group.

[0029] The path analysis module for external water infiltration is used to obtain the length of the water flow path, the coverage area of ​​the water flow, and the elevation difference of the water flow according to the propagation process of the water flow in the connected network of the underground cavern group, calculate the shortest path from the water flow input node to the target node, the maximum spread range of the water flow, and the water flow elevation change diagram, so as to realize the path analysis of external water infiltration in the hydropower station cavern group.

[0030] The risk identification module for external water infiltration is used to perform risk assessment on each node and connecting line of the cavern group water collection network model based on the length of the water flow path, the coverage area of ​​the water flow, and the elevation difference of the water flow spread, so as to realize the risk identification of external water infiltration in the cavern group of the hydropower station.

[0031] The present invention also proposes an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to implement the path analysis and risk identification method for external water infiltration in a hydropower station cavern group as described above.

[0032] The present invention also proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the path analysis and risk identification method for external water infiltration into a hydropower station cavern group as described above.

[0033] Compared with the prior art, the present invention establishes a water catchment network model of an underground cavern group, dynamically simulates the propagation path of water flow, comprehensively evaluates the risk of external water infiltration, and displays the water flow path, thereby realizing comprehensive external water infiltration path analysis and risk identification for complex underground cavern groups. The present invention effectively solves the problems of low accuracy of the risk assessment results of water infiltration in the cavern group of a hydropower station, and the difficulty in accurately predicting the propagation path of the water flow and its affected range, provides a scientific water flow management and protection plan for the hydropower station, and provides scientific technical support for the anti-seepage design, risk management and emergency response of the underground powerhouse of the hydropower station, and has strong practical engineering significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The present invention is a flow chart of the method.

[0035] Figure 2 It is a system architecture diagram of the present invention.

[0036] Figure 3 It is a schematic diagram of the water collection network model of the underground powerhouse cavern group of the hydropower station in the embodiment.

[0037] Figure 4 It is a schematic diagram of dynamic simulation of water flow spreading path in the embodiment.

[0038] Figure 5 Graph showing water flow path and elevation change in the embodiment.

[0039] Figure 6 4 is a risk level determination diagram in the embodiment.

[0040] Figure 7 This is a calculation diagram of the shortest path of water flow in the embodiment. DETAILED DESCRIPTION

[0041] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0042] Path analysis and risk identification method of external water infiltration in hydropower station caverns, the flow chart is as follows Figure 1 As shown, the details are as follows.

[0043] Firstly, according to the structure and connectivity data of the hydropower station cavern group, nodes are used to represent the intersection points of each cavern or channel, and connecting lines are used to represent the underground caverns or channels connecting each node, to construct a cavern group water collection network model.

[0044] Specifically, in the cavern group water collection network model, the attributes of the nodes include: node location, node elevation, node type, and permeability; the node types include caverns, water collection points, and intersections; the attributes of the connecting lines include: line length, slope, undulation, channel cross-sectional dimensions, material properties, and permeability.

[0045] In the construction of the cavern group water collection network model, based on the terrain data, geological conditions, fault distribution and groundwater data of the hydropower station cavern group, according to the hydrodynamics and geological engineering theory, the fluid dynamics equations between nodes and lines are used to describe the movement law of water in complex geological structures, and the connectivity logic diagram of the hydropower station cavern group is generated as the connectivity relationship data of the hydropower station cavern group.

[0046] Then, based on the places where surface water is concentrated or the areas around the cavern groups that are prone to external water infiltration, potential risk points for external water infiltration are selected in the cavern group catchment network model, and external water infiltration-related parameters including rainfall, groundwater level and water flow infiltration are input for each potential risk point.

[0047] Specifically, among the parameters related to external water infiltration, rainfall is obtained through historical rainfall data or real-time meteorological data, groundwater level is the groundwater level affecting infiltration obtained based on groundwater data, and water flow infiltration is set by regional permeability test results and material properties.

[0048] Then, according to the potential risk points of external water infiltration and the relevant parameters of external water infiltration at each potential risk point, the water flow dynamics simulation algorithm was used to analyze the spread path of external water infiltration, and the propagation process of water flow in the connected network of underground caverns was simulated.

[0049] Specifically, the simulation method for the propagation process of water flow in the connected network of underground caverns is:

[0050] Conduct initial water flow distribution simulation: Starting from the selected potential risk points for external water infiltration, simulate how water flows into the underground cavern network and how water flows propagate between nodes and lines based on the influence of gravity, permeability and geological resistance;

[0051] Conduct path propagation analysis: Based on the elevation difference between nodes, the undulation and slope of the line, the water flow preferentially flows to the nodes with lower elevations, determine the flow direction and path of the water flow, and obtain the flow velocity and range of the water flow in each line according to the channel capacity of different lines;

[0052] Perform extended path calculation: The path of water flow starting from the infiltration point, passing through each line and reaching other nodes is calculated through repeated iterations. During the process of water flow spreading, the water flow transmission capacity of each line is calculated to evaluate the farthest range that the water flow may reach.

[0053] Finally, based on the propagation process of water flow in the connected network of the underground cavern group, the length of the water flow path, the coverage area of ​​the water flow and the elevation difference of the water flow spread are obtained. The shortest path from the water flow input node to the target node, the maximum spread range of the water flow and the water flow elevation change diagram are calculated to realize the path analysis of external water infiltration into the hydropower station cavern group.

[0054] Specifically, in the path analysis of water infiltration from outside the hydropower station cavern group, the shortest path is the shortest propagation path from the water flow input node to the target node; the maximum spread range is the maximum range in which the water flow can propagate, that is, the farthest node and connecting line that the water flow may reach; the elevation change map is the elevation change map along the water flow obtained based on the distribution of the water flow at different elevations.

[0055] More specifically, in the path analysis of external water infiltration in the hydropower station cavern group, based on the propagation process of water flow in the connected network of the underground cavern group, the starting point of the water flow, the nodes and lines through which the water flow passes, and the nodes and connected lines affected by the water flow are marked with different colors to show the process of water flow spread and the expansion path and speed of the water flow.

[0056] Finally, based on the length of the water flow path, the coverage area of ​​the water flow, and the elevation difference of the water flow, a risk assessment is conducted on each node and connecting line of the cavern group water collection network model to identify the risk of external water infiltration into the hydropower station cavern group.

[0057] Specifically, in the risk identification of external water infiltration in the hydropower station cavern group, the risk assessment calculation formula is:

[0058] R=α×L+β×A+γ×H,

[0059] In the formula, R is the risk value of each node; L is the length of the water flow path; A is the coverage area of ​​the water flow; H is the elevation difference of the water flow spread; α, β, and γ are all weight coefficients of risk assessment, which are set according to specific engineering experience;

[0060] The risk value of the node is compared with the set threshold, and the node is divided into a low-risk area, a medium-risk area and a high-risk area; the setting of the threshold can be optimized based on historical data analysis, simulation result calibration and dynamic adjustment of the actual environment.

[0061] The path analysis and risk identification system for water infiltration from outside the hydropower station caverns is shown in the following figure. Figure 2 As shown, it consists of a cavern group water collection network model construction module, a potential risk point selection module, an external water infiltration spread path simulation module, an external water infiltration path analysis module, and an external water infiltration risk identification module.

[0062] The cavern group water collection network model construction module is used to construct the cavern group water collection network model based on the structure and connectivity relationship data of the hydropower station cavern group, with nodes representing the intersection points of each cavern or channel, and connecting lines representing the underground caverns or channels connecting each node.

[0063] The potential risk point selection module is used to select potential risk points of external water infiltration in the cavern group water collection network model based on places where surface water is concentrated or areas around the cavern group where external water infiltration is prone to occur, and input external water infiltration related parameters including rainfall, groundwater level and water flow penetration for each potential risk point.

[0064] The external water infiltration spread path simulation module is used to analyze the external water infiltration spread path based on the potential risk points of external water infiltration and the external water infiltration related parameters of each potential risk point, using the water flow dynamics simulation algorithm to simulate the propagation process of water flow in the connected network of the underground cavern group.

[0065] The path analysis module for external water infiltration is used to obtain the length of the water flow path, the coverage area of ​​the water flow, and the elevation difference of the water flow according to the propagation process of the water flow in the connected network of the underground cavern group. It calculates the shortest path from the water flow input node to the target node, the maximum spread range of the water flow, and the water flow elevation change diagram, thereby realizing the path analysis of external water infiltration in the hydropower station cavern group.

[0066] The risk identification module for external water infiltration is used to conduct risk assessment on each node and connecting line of the cavern group water collection network model based on the length of the water flow path, the coverage area of ​​the water flow, and the elevation difference of the water flow spread, so as to realize the risk identification of external water infiltration in the cavern group of the hydropower station.

[0067] The implementation method of each module in the system is consistent with that described in the above method and will not be repeated here.

[0068] The present invention also proposes an electronic device, comprising: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to implement the path analysis and risk identification method for external water infiltration into a hydropower station cavern group and the path analysis and risk identification system for external water infiltration into a hydropower station cavern group as described above.

[0069] The present invention also proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the path analysis and risk identification method for external water infiltration into a hydropower station cavern group and the path analysis and risk identification system for external water infiltration into a hydropower station cavern group as described above.

[0070] Example

[0071] The present invention is used to conduct path analysis and risk identification of external water infiltration in an underground powerhouse cavern group of a hydropower station.

[0072] A water catchment network model of underground caverns is constructed. The model consists of multiple tunnel-connected nodes and caverns, which represent the propagation path of water flow in underground caverns. Figure 3 As shown, the basic connectivity structure and elevation differences of the underground cavern group are demonstrated. Figure 3 In the figure, the circular nodes represent the nodes of the underground caverns of the hydropower station. The cavern is the core structure of the underground powerhouse, which is used to accommodate equipment and passages and constitutes the basic unit of the underground cavern group. The straight lines or curves represent the connecting lines between the cavern nodes, representing tunnels or water flow channels. The cavern groups are interconnected through these lines to form a complex network. The elevation of the nodes is distinguished by color: green represents nodes or caverns with higher elevations, which are the starting points of the water flow. Blue represents nodes of medium height, and the water will flow through these areas and gradually flow to lower places. Black represents low nodes, which are usually the gathering points of water flow and are prone to water accumulation or leakage. Figure 3 It shows the connectivity and elevation differences of the underground cavern complex, but does not involve the direction of water flow.

[0073] Each underground cavern or important water flow intersection is represented as a tunnel-connected node. The geometric properties of the tunnel-connected nodes (such as coordinates and elevation) are determined by terrain exploration data and actual design.

[0074] like Figure 3 As shown in the figure, the tunnel-connected nodes from Node 1 to Node 13 represent different locations of underground caverns or water confluence points. For example, Node 1 is located at a higher terrain and is usually the starting point of the water flow. The water flow spreads from Node 1 to other tunnel-connected nodes. Node 9 is located at a lower terrain and may become a place where water flows converge, which is prone to seepage or water accumulation problems.

[0075] The elevation of the node is determined by terrain exploration data, and the system distinguishes the elevation differences by color: green represents tunnel-connected nodes with higher elevations (such as Node 1); blue represents tunnel-connected nodes with medium elevations (such as Node 3 and Node 5); black represents low tunnel-connected nodes (such as Node 9 and Node 10).

[0076] Tunnels are water channels that connect connected nodes and represent connections between underground chambers. Figure 3In the diagram, tunnels are labeled Cavern 1-2, Cavern 1-3, etc. For example, Cavern 1-2 represents the tunnel connecting Node 1 and Node 2. Water flows along the tunnel from one tunnel-connected node to another. The length, slope, and cross-sectional dimensions of the tunnel determine the velocity and flow rate of the water flow. Longer tunnels may reduce the velocity of the water flow, while wider tunnels can accommodate more water flow.

[0077] Elevation difference is an important factor affecting the propagation path of water flow. The system determines the elevation of nodes and tunnels connected to the tunnels through terrain data and groundwater exploration results. For example, water flows from Node 1 (high point) through Cavern 1-2 and Cavern 2-4 to Node 9 (low point). Geological properties affect the permeability and flow velocity of the tunnel. If the permeability of a tunnel is low, the propagation of water in it will be resisted, affecting the flow rate.

[0078] Through the above steps, a complete water collection network model of the underground powerhouse caverns of the hydropower station is constructed, as shown in the schematic diagram. Figure 3 shown.

[0079] After the cavern group water catchment network model is constructed, the infiltration path of external water flow is simulated to evaluate the propagation path of water flow in the underground cavern group and its impact range after external water infiltration. The dynamic simulation diagram of the water flow propagation path is shown in the figure. Figure 4 As shown, it shows the process of water flow spreading from the starting point to other tunnel connected nodes.

[0080] Figure 4 In the figure, the circular nodes represent the nodes of the underground caverns, and each node may become the inflow or outflow point of the water flow. The arrows clearly indicate the flow direction of the water flow, and the water flow spreads from the starting point (green node) to other nodes along the path indicated by the arrow. The green node represents the starting point of the water flow, which is usually the entrance for external water flow to enter the underground network. The blue path represents the area affected by the water flow. The water flow will spread to these nodes, indicating that these nodes are affected by the water flow. The black nodes represent the areas not affected by the water flow, and these nodes are temporarily safe. Figure 4 The arrows clearly show the starting point and diffusion path of the water flow.

[0081] The external water infiltration points are set as follows: The external water infiltration points are usually located above or around the surface area of ​​the underground caverns. The system simulates the infiltration of external water caused by rainfall or groundwater level changes by setting external water infiltration points. Figure 4 In the example, Node 1 is set as the external water infiltration point. The external water flow starts from Node 1 and gradually spreads to other nodes connected to the tunnel through the tunnel. The water flow first enters the tunnel Cavern 1-2 and spreads to Node 2, and then continues to spread to lower nodes.

[0082] The simulation of the water flow propagation path is as follows: According to the starting point of the water flow and the physical properties of the tunnel, the water flow propagation path is dynamically simulated. The water flow path and elevation change diagram are shown in Figure 5 shown.

[0083] Figure 5 In the figure, the circular nodes mark the path of water flow from high to low, and each node is marked green, blue or black according to its elevation. The elevation difference is distinguished by color, with green representing high points, blue representing intermediate elevations, and black representing low points. The curved path indicates that the water flow passes through caverns at different elevations, gradually spreading from high to low. The path of the water flow reflects the natural trend under the action of gravity. Figure 5 Shows the changes in elevation of water flowing through the cavern network.

[0084] like Figure 5 As shown in the figure, the water flows from Node 1, spreads along Cavern 1-2 to Node 2, and then flows along Cavern 2-4 to Node 4 and other nodes. The flow rate in each tunnel is determined by the length and slope of the tunnel. The areas affected by the water flow are distinguished by color: blue nodes represent nodes connected to the tunnels through which the water flows (such as Node 2 and Node 4); black nodes represent nodes that are not affected (such as Node 9 and Node 10).

[0085] After the external water infiltration simulation, the risk level of each tunnel connection node is determined according to the water flow range, path length and elevation difference. The risk level determination diagram is shown in the figure below: Figure 6 As shown, the risk division and water flow path of each node are displayed.

[0086] Figure 6 In the figure, circular nodes represent risk areas in the underground cavern network, and the node colors are divided according to the risk level of water flow: red represents high-risk areas, where water flow may accumulate and cause danger; yellow represents medium-risk areas, where there is a certain risk when water flows through these nodes; green represents low-risk areas, where water flow is not likely to affect these nodes and is usually in a safe state. Arrows indicate the spread of water flow from high-risk areas to low-risk areas, helping to identify the flow trend and potential risk range of water flow. Figure 6 The arrows clearly show the path of risk transmission from high risk to low risk.

[0087] like Figure 6As shown in the figure, the nodes connected to the tunnel are divided into different risk levels, which are determined according to the influence range of the water flow and the node location. Red nodes (such as Node 9) represent high-risk areas, where water flows are likely to gather and cause leakage; yellow nodes (such as Node 5) represent medium-risk areas, where risks may arise when water flows through; green nodes (such as Node 1) represent low-risk areas, where water flows are not likely to affect these nodes and are usually in a safe state. By analyzing the propagation path of the water flow and the risk level of the node, a risk path map is generated to help engineering personnel identify the propagation trend of water flow from high-risk areas to low-risk areas, such as Figure 6 As shown, water flow propagates from the red high-risk areas to the yellow and green nodes, with the arrows showing this trend.

[0088] Calculate the shortest path of water flow in the tunnel network after external water infiltration, so as to ensure that the propagation path and impact range of water flow can be quickly identified, such as Figure 7 As shown, the shortest path for water flow is shown.

[0089] Figure 7 In the figure, the circular nodes represent the key nodes on the water flow path. The red arrows represent the shortest path of the water flow, which is the shortest propagation route of the water flow from the starting point to the target node. The blue arrows represent other paths of the water flow. Although they are not the shortest paths, the water flow may still spread to these nodes. Figure 7 Arrows are used to show the shortest path for water flow and other possible spread paths, helping engineers prioritize areas with greater water flow risks.

[0090] like Figure 7 As shown in the figure, the algorithm calculates the shortest path of water flow from the external water infiltration point to the nodes connected to each tunnel. The red arrows indicate the shortest path, and the blue arrows indicate other possible water flow paths. For example, the water flows from Node 1, passes through Cavern 1-2 and Cavern 2-4, and reaches Node 9 by the shortest path. This diagram helps engineers prioritize areas with greater water flow risks and ensure the safety of the underground powerhouse of the hydropower station.

[0091] Through the above, the construction of the water network model, dynamic simulation of water flow, risk assessment and shortest path calculation of the underground powerhouse cavern group of the hydropower station were realized, providing a scientific water flow management and protection plan for the hydropower station.

[0092] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of complete hardware embodiment, complete software embodiment, or the embodiment in combination with software and hardware. Moreover, the application can adopt the form of the computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java, C++, Python and literal scripting language JavaScript, etc.

[0093] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0094] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0095] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0096] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0097] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. The path analysis and risk identification method of water infiltration from outside the hydropower station caverns is characterized by: include: According to the structure and connectivity data of the hydropower station caverns, nodes are used to represent the intersections of caverns or channels, and connected lines are used to represent the underground caverns or channels connecting the nodes, so as to construct a cavern group water catchment network model. Based on the areas where surface water is concentrated or the areas around the caverns that are prone to external water infiltration, select the potential risk points of external water infiltration in the cavern catchment network model, and input the external water infiltration related parameters including rainfall, groundwater level and water flow penetration for each potential risk point; According to the potential risk points of external water infiltration and the parameters related to the external water infiltration at each potential risk point, the propagation path of external water infiltration is analyzed using the hydraulic flow dynamics simulation algorithm to simulate the propagation process of water flow in the connected network of underground caverns. According to the propagation process of water flow in the connected network of underground caverns, the length of the water flow path, the coverage area of ​​the water flow and the elevation difference of the water flow spread are obtained. The shortest path from the water flow input node to the target node, the maximum spread range of the water flow and the water flow elevation change diagram are calculated to realize the path analysis of the external water infiltration of the hydropower station cavern group; Based on the length of the water flow path, the coverage area of ​​the water flow, and the elevation difference of the water flow, a risk assessment is conducted on each node and connecting line of the cavern group water collection network model to identify the risk of external water infiltration into the hydropower station cavern group.

2. The method for path analysis and risk identification of water infiltration from outside the hydropower station cavern group according to claim 1 is characterized by: In the cavern group water collection network model, the attributes of the nodes include: node location, node elevation, node type, and permeability; the node types include caverns, water collection points, and intersection points; In the cavern group water collection network model, the attributes of the connected lines include: line length, slope, undulation, channel cross-sectional dimensions, material properties, and permeability; In the construction of the cavern group water collection network model, based on the topographic data, geological conditions, fault distribution and groundwater data of the hydropower station cavern group, according to the hydrodynamics and geological engineering theory, the movement law of water flow in the complex geological structure is described by the fluid dynamics equation between the nodes and the lines, and the connectivity logic diagram of the hydropower station cavern group is generated, which is used as the connectivity relationship data of the hydropower station cavern group.

3. The method for path analysis and risk identification of water infiltration outside a hydropower station cavern group according to claim 2 is characterized by: Among the parameters related to external water infiltration, rainfall is obtained through historical rainfall data or real-time meteorological data, groundwater level is the groundwater level affecting infiltration obtained based on groundwater data, and water flow infiltration is set by regional permeability test results and material properties.

4. The method for analyzing the path of water infiltration from outside the caverns of a hydropower station according to claim 3 is characterized by: The method for simulating the propagation process of the water flow in the connected network of the underground cavern group includes: Conduct initial water flow distribution simulation: Starting from the selected potential risk points for external water infiltration, simulate how water flows into the underground cavern network and how water flows propagate between nodes and lines based on the influence of gravity, permeability and geological resistance; Conduct path propagation analysis: Based on the elevation difference between nodes, the undulation and slope of the line, the water flow preferentially flows to the nodes with lower elevations, determine the flow direction and path of the water flow, and obtain the flow velocity and range of the water flow in each line according to the channel capacity of different lines; Perform extended path calculation: The path of water flow starting from the infiltration point, passing through each line and reaching other nodes is calculated through repeated iterations. During the process of water flow spreading, the water flow transmission capacity of each line is calculated to evaluate the farthest range that the water flow may reach.

5. The method for analyzing the path of water infiltration from outside the caverns of a hydropower station according to claim 4 is characterized by: In the path analysis of water infiltration from outside the hydropower station cavern group, the shortest path is the shortest propagation path from the water flow input node to the target node; the maximum spreading range is the maximum range in which the water flow can propagate, that is, the farthest node and connecting line that the water flow may reach; the elevation change map is the elevation change map of the water flow along the way obtained based on the distribution of the water flow at different elevations.

6. The method for path analysis and risk identification of water infiltration outside a hydropower station cavern group according to claim 5 is characterized by: In the path analysis of water infiltration from outside the hydropower station cavern group, based on the propagation process of water flow in the connected network of the underground cavern group, the starting point of the water flow, the nodes and lines through which the water flow passes, and the nodes and connected lines affected by the water flow are marked with different colors to show the process of water flow spread and the expansion path and speed of the water flow.

7. The method for path analysis and risk identification of water infiltration outside a hydropower station cavern group according to claim 6 is characterized by: In the risk identification of water infiltration outside the hydropower station cavern group, the risk assessment calculation formula is: R=α×L+β×A+γ×H, In the formula, R is the risk value of each node; L is the length of the water flow path; A is the coverage area of ​​the water flow; H is the elevation difference of the water flow spread; α, β, and γ are all weight coefficients of risk assessment, which are set according to specific engineering experience; The risk value of the node is compared with the set threshold, and the node is divided into a low-risk area, a medium-risk area and a high-risk area; the setting of the threshold can be optimized based on historical data analysis, simulation result calibration and dynamic adjustment of the actual environment.

8. A path analysis and risk identification system for water infiltration outside a hydropower station cavern group implementing the method described in any one of claims 1 to 7, characterized in that: It includes a cavern group water catchment network model construction module, a potential risk point selection module, an external water infiltration spread path simulation module, an external water infiltration path analysis module, and an external water infiltration risk identification module; The cavern group water catchment network model construction module is used to construct a cavern group water catchment network model based on the structure and connectivity relationship data of the hydropower station cavern group, with nodes representing the intersection points of each cavern or channel, and with connected lines representing the underground caverns or channels connecting each node; The potential risk point selection module is used to select potential risk points of external water infiltration in the cavern group water catchment network model based on places where surface water is concentrated or areas around the cavern group where external water infiltration is likely to occur, and input external water infiltration related parameters including rainfall, groundwater level and water flow infiltration for each potential risk point; The external water infiltration spreading path simulation module is used to analyze the spreading path of external water infiltration using a hydrodynamic simulation algorithm based on the potential risk points of external water infiltration and the external water infiltration amount-related parameters of each potential risk point, and simulate the propagation process of water flow in the connected network of the underground cavern group; The path analysis module for external water infiltration is used to obtain the length of the water flow path, the coverage area of ​​the water flow, and the elevation difference of the water flow according to the propagation process of the water flow in the connected network of the underground cavern group, calculate the shortest path from the water flow input node to the target node, the maximum spread range of the water flow, and the water flow elevation change diagram, so as to realize the path analysis of the external water infiltration of the hydropower station cavern group; The risk identification module for external water infiltration is used to perform risk assessment on each node and connecting line of the cavern group water collection network model based on the length of the water flow path, the coverage area of ​​the water flow, and the elevation difference of the water flow spread, so as to realize the risk identification of external water infiltration in the cavern group of the hydropower station.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor implements the path analysis and risk identification method for external water infiltration into a hydropower station cavern group as described in any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the path analysis and risk identification method for external water infiltration into a hydropower station cavern group as described in any one of claims 1 to 7 is implemented.

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