Hydropower station underground powerhouse water flooding fault rapid simulation prediction method and prediction system

Abstract

This invention relates to the field of hydropower station safety technology, and discloses a rapid simulation and prediction method for flooding faults in underground powerhouses of hydropower stations, comprising the following steps: S1: Constructing a rapid simulation analysis model, the parameter system of which includes geometric parameters, hydraulic parameters, and disaster parameters; S2: Dividing the underground powerhouse space of the rapid simulation analysis model into multiple reservoirs and establishing a water balance equation; S3: Calculating the drainage capacity of the drainage system of the rapid simulation analysis model; S4: Establishing a leakage risk point seepage model of the rapid simulation analysis model and calculating the inflow rate; S5: Based on the mass conservation equation and momentum conservation equation, using a time-stepping algorithm to simulate the entire process from initial seepage to complete flooding, and outputting the predicted simulation results. This invention accurately simulates and predicts the inflow rate and water level elevation into the powerhouse based on the spatial structural characteristics of the underground powerhouse, thereby improving the accuracy and speed of emergency decision-making.

Description

Technical Field

[0001] This invention relates to the field of hydropower station safety technology, and in particular to a rapid simulation and prediction method and system for flooding faults in underground powerhouses of hydropower stations. Background Technology

[0002] The hydropower industry has always attached great importance to preventing powerhouse flooding. However, in recent years, flooding accidents caused by natural disasters or equipment failures have continued to occur, resulting in significant economic losses and even casualties for hydropower stations. Due to its immense destructive powerhouse impact and far-reaching social consequences, flooding is a key safety hazard that hydropower stations should prioritize preventing. The severe consequences of hydropower station flooding accidents underscore the importance and necessity of preventative measures. To prevent powerhouse flooding, it is essential to identify potential risks, pinpoint the hazardous factors and their causal mechanisms, and implement corrective measures, both engineering and non-engineering, to address the accident's development path and stages, breaking the chain of events and preventing the accident from occurring. Historical cases of flooding often demonstrate that the development of a powerhouse flooding incident can occur very rapidly, often within minutes. In actual flooding accident assessment and response scenarios, a rapid and accurate response is a primary requirement guiding engineering practice. In order to understand the dangerous factors and causal mechanisms of flooded factory buildings, it is necessary to conduct simulation and prediction studies on the accident development path caused by flooded factory building failures and to develop rapid and accurate response plans to support the requirements of rapid and accurate emergency decision-making and response.

[0003] Existing technology 1:

[0004] Current research on flood-prone power plant simulations is mostly qualitative. A few quantitative studies only analyze the relative relationship between the inflow of water into the plant and the drainage capacity of the pumping system, thus determining the flood elevation of the plant under balanced water conditions. However, these studies fail to reflect the changing patterns of flood-prone power plant accidents with different risk points and operating conditions, and cannot effectively integrate with power plant monitoring information to provide technical support for the forecasting and early warning of flood-prone power plant accidents.

[0005] Existing technology 2:

[0006] While existing 3D CFD numerical simulation models with constant-size models can depict the evolution process very precisely, their large computational grid and huge computational load pose objective difficulties in practical engineering applications, especially in scenarios that require rapid and accurate prediction of response at the minute level and quick recommendations for emergency response plans.

[0007] Therefore, the technical problems existing in the current technology can be summarized as follows:

[0008] The analysis of working conditions and the accuracy of the calculation results are limited, and the calculation time is too long to be real-time feasible, so it cannot provide rapid and effective technical support for the prediction and early warning of flooded factory accidents. Summary of the Invention

[0009] To address the challenge of rapid simulation and prediction of accidents caused by powerhouse flooding, and to support emergency decision-making and response in hydropower stations, this invention provides a rapid simulation prediction method and a real-time evaluation and decision support system. The core of this simulation prediction method is to fully consider the spatial structural characteristics of the underground powerhouse and accurately simulate and predict macroscopic information such as the infiltration flow rate and water level elevation, which are of paramount importance for emergency decision-making and response. Based on this key information, a real-time evaluation and decision support system is constructed to provide a rapid response plan for emergency decision-making in response to powerhouse flooding accidents.

[0010] This invention provides the following technical solution:

[0011] A rapid simulation and prediction method for flooding faults in underground powerhouses of hydropower stations includes the following steps:

[0012] S1: Construct a rapid simulation analysis model. The parameter system of the rapid simulation analysis model includes geometric parameters, hydraulic parameters, and disaster parameters. The geometric parameters are used to describe the structural characteristics of the plant space, the hydraulic parameters are used to reflect the flow energy dissipation characteristics, and the disaster parameters are used to characterize the time-varying input of disaster triggering conditions.

[0013] S2: Based on the principle of water storage tanks, the underground powerhouse space of the hydropower station in the rapid simulation analysis model is divided into multiple water storage tanks, and a water balance equation is established for each water storage tank to simulate water level changes and water circulation between water storage tanks.

[0014] S3: Calculate the drainage capacity of the drainage system in the rapid simulation analysis model, including determining the drainage flow rate based on the pump response curve, and considering the phased drainage scheme and mobile drainage equipment;

[0015] S4: Establish the leakage risk point leakage model of the rapid simulation analysis model, calculate the influent flow rate, and the calculated influent flow rate includes the dynamic flow rate during the dynamic closing process of the gate or blade and the steady-state flow rate after the gate or blade is completely closed.

[0016] S5: Based on the mass conservation equation and momentum conservation equation, the time step algorithm is used to simulate the entire process from initial leakage to complete flooding, and output the predicted simulation results, including water level-time curves, flooding isochrones, and flow velocity vector fields.

[0017] According to some implementation methods, the geometric parameters include the geometric structural parameters of the factory space and the dimensions of the connecting openings, which include the dimensions of doorways, pipes, or shafts.

[0018] According to some implementation methods, the hydraulic parameters include a roughness coefficient and a local loss coefficient. The roughness coefficient is determined based on the surface material partitioning, and the local loss coefficient is calculated based on the gate groove, sudden expansion or sudden contraction structure.

[0019] According to some implementation methods, the disaster parameters include the time history of external water infiltration flow, the area of ​​the burst pipe opening, and the effective head.

[0020] According to some implementation methods, in step S3, the drainage capacity calculation of the drainage system also includes dividing the collection well into a separate water storage tank and simulating the water level change of the collection well to determine the drainage flow rate.

[0021] According to some implementation methods, in step S4, the leakage risk point leakage model calculates the dynamic closing process and steady-state process of the inflow based on the gate state and outflow conditions. The dynamic closing process considers the pressure of the upstream reservoir or downstream river, and the steady-state process considers the water accumulated in the water diversion tunnel or tailrace tunnel as the water source.

[0022] According to some implementation methods, the time stepping algorithm simulates with second-level precision and outputs information on the rise of water level over time, the inundation range, and the preferred path of water flow.

[0023] On the other hand, the present invention also provides a rapid simulation and prediction system for flooding faults in underground powerhouses of hydropower stations, comprising:

[0024] The construction module is used to build a rapid simulation analysis model. The parameter system of the rapid simulation analysis model includes geometric parameters, hydraulic parameters, and disaster parameters. The geometric parameters are used to describe the structural characteristics of the plant space, the hydraulic parameters are used to reflect the flow energy dissipation characteristics, and the disaster parameters are used to characterize the time-varying input of disaster triggering conditions.

[0025] The reservoir module is used to divide the underground powerhouse space of the hydropower station into multiple reservoirs based on the reservoir principle and the rapid simulation analysis model, and to establish a water balance equation for each reservoir to simulate water level changes and water circulation between reservoirs.

[0026] The drainage module is used to calculate the drainage capacity of the drainage system in the rapid simulation analysis model, including determining the drainage flow rate based on the pump response curve, and considering the phased drainage scheme and mobile drainage equipment.

[0027] The leakage module is used to establish the leakage risk point seepage model of the rapid simulation analysis model and calculate the inflow rate. The calculated inflow rate includes the dynamic flow rate during the dynamic closing process of the gate or blade and the steady-state flow rate after the gate or blade is completely closed.

[0028] The simulation module is used to simulate the entire process from initial leakage to complete flooding based on the mass conservation equation and momentum conservation equation using a time-stepping algorithm, and outputs predicted simulation results, including water level-time curves, flooding isochrones, and flow velocity vector fields.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. Addressing the limitations of existing methods mentioned in the background section, such as limited operating condition types and inability to effectively integrate with power plant monitoring information, the parametric model system (including geometric, hydraulic, and disaster parameters) constructed in this invention possesses high flexibility and can quickly adapt to different risk points and operating conditions. It overcomes the limitations of existing quantitative research methods that rely on single operating conditions and cannot be linked with monitoring systems, achieving accurate forecasting and early warning based on real-time operating conditions.

[0031] 2. Addressing the objective difficulty mentioned in the background art—the massive computational demands of 3D CFD models, which cannot meet the requirements of minute-level emergency response—this invention greatly simplifies the computational model by employing a dynamic volumetric model and parameterization system based on the "reservoir principle." Simultaneously, combined with a time-progression algorithm with a second-step size, it can complete the dynamic simulation of the entire process from initial leakage to complete flooding in an extremely short time while ensuring the accuracy of calculations for key macroscopic parameters (such as water level and flow rate). This successfully resolves the technical contradiction of balancing "real-time performance" and "accuracy" in simulation prediction, meeting the primary requirement of minute-level rapid response in emergency decision-making.

[0032] 3. Based on the rapid and accurate simulation capabilities of the rapid simulation prediction method provided in this application, the method and model can access or integrate actual hydrological monitoring information from the power plant (such as gate status, initial water level, pipe burst signals, etc.) as initial simulation conditions or dynamic inputs, thereby making rapid simulation predictions based on the current real conditions of the power plant. It can quickly complete prediction and assessment in the early stages of an accident, fully meeting the urgent requirements for minute-level rapid and accurate prediction and response during the evolution of a flooded power plant accident.

[0033] 4. The prediction method and system constructed in this invention can serve as a core analysis and decision support module in the monitoring and emergency response system for flooded powerhouses in hydropower stations, enhancing the systematic nature and practicality of analysis and decision-making. It can provide direct emergency operational guidance for breaking the chain of accidents. Its output of key information such as water level-time curves, flood isochronous maps, and flow velocity vector fields can be directly used to assess accident consequences, identify priority water flow paths, formulate optimal drainage scheduling plans, and plan personnel rescue routes. This provides quantitative and intuitive real-time decision support services for operators to take engineering and non-engineering measures to "break the chain of accidents," ultimately effectively preventing accidents or mitigating accident losses. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of a three-dimensional spatial structure model of a hydropower station's underground powerhouse water diversion and power generation system provided in an embodiment of the present invention.

[0035] Figure 2 This is a schematic diagram of the process for establishing a rapid simulation analysis model provided in an embodiment of the present invention.

[0036] Figure 3 This is the simulation calculation result of the water level change over time in the underground powerhouse space under the simulated scenario of flooding failure and emergency intervention in drainage of a hydropower station, provided by an embodiment of the present invention.

[0037] Figure 4 This is an example of a simulation prediction and decision-making support system for hydropower plant flooding accidents provided in this embodiment of the invention.

[0038] In the picture:

[0039] Main plant space 1; water pressure steel pipe 2. Detailed Implementation

[0040] Flooded powerhouse failures, due to their immense destructive power and far-reaching social impact, represent a key safety hazard that hydropower stations should prioritize for prevention. Historical cases of flooded powerhouses demonstrate that their development is often rapid, occurring within minutes. An analytical model based on a simplified dynamic volumetric model offers greater practical value for rapid engineering-level evaluation. Comparative studies show that the simplified model and the 3D simulation model have acceptable computational errors in macroscopic parameters. Establishing a rapid engineering-level evaluation methodology for flooded powerhouse failures based on the dynamic volumetric model can achieve rapid analysis and evaluation decision-making for these failures while maintaining a certain level of accuracy.

[0041] The present invention will now be described in detail with reference to embodiments and accompanying drawings. However, it should be understood that the embodiments and drawings are for illustrative purposes only and do not constitute any limitation on the scope of protection of the present invention. All reasonable modifications and combinations included within the inventive spirit of the present invention fall within the scope of protection of the present invention.

[0042] The present invention will be further described below with reference to the accompanying drawings.

[0043] Example 1

[0044] In this embodiment, for example, Figure 1 The figure shows the three-dimensional spatial structure of the underground powerhouse water diversion and power generation system of a hydropower station. The location of the main powerhouse space 1 and the water diversion pressure steel pipe 2 is shown in the figure. The rapid simulation prediction and emergency decision-making process for flooding of the powerhouse after the water diversion pressure steel pipe 2 bursts is as follows:

[0045] S1: Parameter system for constructing a rapid simulation analysis model

[0046] Collect the design drawings and technical data of the hydropower station to build the basic database for the model. Geometric parameters can be obtained through BIM model analysis or constructed from the powerhouse design drawings, including the sump, turbine floor of the main powerhouse, generator floor of the main powerhouse, busbar corridors, and other connecting passages. Establish V(h) functions at certain elevation intervals; for example, the spiral casing layer has an asymmetric "S"-shaped curve, requiring consideration of equipment footprint deduction. Consider the dimensions of the portal openings (width × height), sill elevation, opening and closing trajectory envelope (such as the motion equation of floodgates), pipe inner diameter, directional inclination angle (affecting the gravity flow component), flange connection reduction ratio, and the equivalent diameter, depth, and projected area of ​​internal platform protrusions of the connecting openings. Construct detailed functional relationships between the cross-sectional area and height of the powerhouse, and between the water volume and height. Based on the technical data, set the roughness coefficient n for each part of the main powerhouse space, and the local loss coefficient K for sudden expansion / contraction structures of connecting openings, etc. Assume the burst point of the water intake steel pipe is located behind the emergency gate and in front of the guide vane, with a leakage elevation of 358m and a leakage area of ​​1.77m². 2 (A circle with a diameter of 1.5m). The gate was operating normally before the leak; the emergency gate, guide vanes, and tailrace gate were all open. They began to close after the leak was detected.

[0047] S2: Space division based on the principle of water storage tank

[0048] The complex underground powerhouse space is divided into multiple reservoir spaces. In this embodiment, the powerhouse space is divided into five reservoirs. From the bottom of the powerhouse upwards, they are reservoir I, reservoir II, reservoir III, reservoir IV, and reservoir V. Reservoir I mainly contains maintenance and drainage corridors. Reservoir II mainly contains the spiral casing layer and maintenance and drainage corridors. Reservoir III mainly contains the turbine layer. Reservoir IV is mainly the busbar tunnel layer. Reservoir V is mainly the generator layer and the space above.

[0049] After dividing the reservoir into sections, the relationship between the cross-sectional area of ​​the reservoir and elevation was further quantified. Due to the varying complexity of different spaces within the plant, different methods were employed to reduce time costs. For more complex water storage spaces within the plant, 3D modeling software such as SolidWorks and SketchUp were used to create detailed models of the plant, and the cross-sectional area at corresponding elevations was read, such as the reduction section of the inlet. For simpler water storage spaces, the relationship between cross-sectional area and height was directly extracted from CAD drawings, such as large cubic spaces like the generator floor and turbine floor.

[0050] S3: Calculate the drainage capacity of the drainage system

[0051] During drainage, the actual head of the pump changes from low to high, and the drainage flow rate decreases accordingly. Assuming a constant pump power, the actual drainage flow rate Q of a single pump at time t is negatively correlated with the head H. Therefore, the formulas describing the drainage flow rate and drainage time can be derived as follows:

[0052] (1)

[0053] (2)

[0054] In the above formula, Q is the rated flow rate of the water pump, H is the rated head of the water pump, V is the water volume, and a and b are constants.

[0055] In this embodiment, the drainage system consists of a total of 8 water pumps, each with a design flow rate of 1250 m³ / h. 3 / h. In the simulation, the water level in the sump is monitored in real time. As the water level in the plant rises, the sump water level and the pump head also increase accordingly. The actual drainage flow rate is dynamically calculated based on the real-time pump head using a lookup table or fitted formula. The emergency plan also includes activating two mobile drainage vehicles, each providing additional drainage capacity. This plan, as a phased drainage strategy, can be triggered in the simulation to evaluate its effectiveness.

[0056] S4: Establish a leakage risk point model

[0057] The calculation of inflow rate needs to be broken down according to the gate status and outflow conditions. In the event of a leakage accident in the hydropower plant, the upstream emergency gate, turbine guide vanes, and tailrace maintenance gate should generally be closed immediately. The calculation of inflow rate is divided into two processes: the dynamic closing process of the gate or vanes and the steady-state process after the gate or vanes are completely closed.

[0058] During the gate closure process, the leak orifice is subjected to pressure from the upstream reservoir or downstream river. Since the cross-sectional area of ​​the reservoir or river is significantly larger than that of the leak orifice, the water level fluctuations in the reservoir or river can be ignored. During this process, when the powerhouse water level does not submerge the leak orifice, the free outflow formula from engineering fluid mechanics is used:

[0059] (3)

[0060] In the above formula: Q is the leakage flow rate, m 3 / s;C d To account for frictional losses and cross-sectional shrinkage, the flow coefficient is denoted by A, where A is the area of ​​the leakage orifice (m²). 3 h represents the water surface elevation of the upstream reservoir or downstream river, in meters. l Let m be the elevation of the leak orifice, and g be the acceleration due to gravity. Once the powerhouse water level submerges the leak orifice, the orifice submersion outflow calculation formula from engineering fluid mechanics can be used, with the powerhouse water level h as the reference value.p The elevation h of the replacement leak hole l .

[0061] After the gate is completely closed, the upstream water source becomes either a diversion tunnel or a tailrace tunnel. In this case, the water level fluctuations in the diversion tunnel or tailrace tunnel cannot be ignored, and the flow velocity cannot be considered zero; instead, it is calculated using the continuity equation. For leaks that are not submerged, the formula for calculating the leakage flow rate Q is derived using Bernoulli's equation and the continuity equation:

[0062] (4)

[0063] In the above formula, A0 is the cross-sectional area of ​​the water diversion tunnel or tailrace tunnel, in m². 2 h t The water level in the intake or tailrace tunnel is given in meters; other parameters remain the same as in the above formula. When the leak hole is submerged in the powerhouse water, the powerhouse water level under submersion conditions, h, is used. p Replace h l .

[0064] S5: Full-process dynamic simulation and result output

[0065] The reservoir model divides the groundwater-flooded space into multiple reservoirs, assuming that water can circulate among them. Based on the mass and momentum conservation equations, the water level changes in each reservoir and the flow rate of the circulating water between them are calculated. Hydropower station underground powerhouses have complex spatial structures with multiple water storage spaces and numerous flood intrusion paths. The reservoir model allows for individual analysis of the flooding situation in each storage space. A dynamic volumetric model is constructed based on the reservoir model principles to simulate flood intrusion paths. The powerhouse is divided into five reservoirs, and a water balance equation is used to simulate water level changes in each reservoir. The water balance formula is as follows:

[0066] (5)

[0067] Discretizing equation (5) yields the following water level iteration formula:

[0068] (6)

[0069] In the formula: h(n+1) and h(n) are the water levels in the reservoir at times n+1 and n, respectively, in meters (m).

[0070] Q in (n) represents the flow rate from outside the factory building into the factory building at time n, m 3 / s;

[0071] Q out (n) represents the flow rate from the simulated reservoir to the outside of the plant at time n, m3 / s;

[0072] A(h(n)) is the cross-sectional area of ​​the factory building corresponding to the water level in the reservoir at time n, in meters. 2 ;

[0073] Δt is the time step, which is taken as 0.01s in this embodiment.

[0074] Considering the flow interaction between the corresponding space and adjacent reservoirs, the water level iteration formula is obtained as follows:

[0075] (7)

[0076] In the formula, Q ins (n) represents the flow rate from the adjacent reservoir into the simulated reservoir at time n, m 3 / s;Q outs (n) represents the flow rate from the simulated reservoir to the adjacent reservoir at time n, m 3 / s;

[0077] The other three rules for water tank flow interaction:

[0078] 1. The flow from the previous floor to this floor is via stairs. The calculation formula is as follows:

[0079] (8)

[0080] In the above formula, h is the water level of the previous level, b is the water passage width of the stairwell of the previous level, and C... d To account for frictional losses and cross-sectional shrinkage, the flow coefficient is taken as 0.78 based on the Reynolds number of the leakage orifice.

[0081] 2. The next level is completely submerged, and excess water from the next level will flow into this level. When calculating this flow rate, a water volume analysis is performed on the next level, Q. in -Q out Excess water will flow into the next level.

[0082] 3. Water leakage has occurred at this level. The leakage is from outside the factory building. The inflow rate is calculated using the seepage flow rate in S4.

[0083] The overall framework of the dynamic volumetric model of a flooded factory building, constructed based on the principle of a water storage tank model, is as follows: Figure 2 As shown, the model consists of three parts: computation, input, and output.

[0084] In the input section, the first input is the relationship between the cross-sectional area of ​​the underground powerhouse and its height, i.e., the A(H) function. The second input is the inflow rate Q under a leakage fault. in (t). The third input is the drainage capacity Q of the drainage system.out (t). In the calculation section, a model is constructed based on the water balance equation and combined with the reservoir model, and the dynamic simulated water level is analyzed by discrete calculation. In the model output section, the analysis and calculation results are presented in the form of water level-time curves and the trend of flow rate change over time in the plant space.

[0085] This embodiment performs rapid simulation calculations on the process of a water flooding accident caused by a burst of the pressure steel pipe in front of the turbine guide vane. An example of the simulation results is shown in the attached figure. Figure 3 As shown (refer to the S1 parameter settings for the simulated operating conditions), the fault point of the pressure steel pipe burst is located after the emergency gate and before the guide vane; the gate was in normal operation before the leakage, and the emergency gate, guide vane, and tailrace gate were all in the open state. After the leakage was detected, they began to close.

[0086] In this scenario, the influent flow rate is divided into two distinct phases. Phase 1 corresponds to the situation where the emergency gate is not fully closed within the first 150 seconds, and the leakage originates from the upstream reservoir. From activation to 95 seconds, the water level inside the powerhouse does not submerge the leak hole. During this period, since fluctuations in the upstream reservoir water level are not considered, the influent flow rate remains essentially constant. From 95 seconds to 150 seconds, when the powerhouse water level submerges the leak hole, the influent flow changes from free outflow to submerged outflow. Phase 2 begins after the emergency gate is fully closed. From 150 seconds to 904 seconds, the outflow is submerged. Around 904 seconds, when the water level in the diversion tunnel equals the rising water level in the powerhouse, the influent flow rate entering the powerhouse is considered zero.

[0087] Simulation results show that the water level in the main plant rose rapidly after the accident, submerging the first reservoir space (maintenance drainage corridor) in about 1 minute and reaching the busbar tunnel level in about 10 minutes. This curve directly provides the critical time window for emergency evacuation and equipment protection. Using the flow rate variation pattern, information such as inundation isochrones, displayed as a two-dimensional plan view, can also be obtained, clearly marking the submerged areas of the plant at different time points. For example, the diagram shows that the floodwaters had spread to the busbar tunnel through the tunnel openings in about 10 minutes.

[0088] The application of decision support is explained below:

[0089] Two crucial parameters for rescue operations are rescue time and rescue flow rate. Based on these, the system distinguishes between two scenarios. Given the maximum permissible inundation height of the power station, the first scenario involves inputting the power station's "estimated rescue time," and the system automatically calculates the minimum rescue flow rate required to meet the inundation height requirement. The second scenario involves inputting the power station's "existing drainage capacity," and the system automatically calculates the latest rescue time required to meet the inundation height requirement.

[0090] The power plant's drainage process is related to the water level inside the plant. The system can automatically generate different drainage plans for different time periods based on the calculated relationship between water level and time, providing more options for emergency rescue measures. The recommended plan consists of drainage methods and a drainage flow rate versus time curve. The drainage methods will display the drainage methods for different time periods under two conditions: "known rescue time" and "known drainage flow rate," and will also plot the drainage flow rate versus time curves for both conditions. Figure 4 As shown.

[0091] Based on the simulation results above, the system can immediately generate recommended plans for decision support, such as:

[0092] Rescue strategy: Based on the flood isochrone map, delineate danger zones and safe evacuation routes, and recommend that personnel located in the bus corridor evacuate within 10 minutes.

[0093] Early warning issuance: The water level-time curve is compared with the installation elevation of key equipment (such as generators and control cabinets) to achieve graded early warning (such as "attention", "warning" and "serious").

[0094] The above embodiments are merely preferred embodiments of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A rapid simulation and prediction method for flooding faults in underground powerhouses of hydropower stations, characterized in that: Includes the following steps: S1: Construct a rapid simulation analysis model. The parameter system of the rapid simulation analysis model includes geometric parameters, hydraulic parameters, and disaster parameters. The geometric parameters are used to describe the structural characteristics of the plant space, the hydraulic parameters are used to reflect the flow energy dissipation characteristics, and the disaster parameters are used to characterize the time-varying input of disaster triggering conditions. S2: Based on the principle of water storage tanks, the underground powerhouse space of the hydropower station in the rapid simulation analysis model is divided into multiple water storage tanks, and a water balance equation is established for each water storage tank to simulate water level changes and water circulation between water storage tanks. S3: Calculate the drainage capacity of the drainage system in the rapid simulation analysis model, including determining the drainage flow rate based on the pump response curve, and considering the phased drainage scheme and mobile drainage equipment; S4: Establish the leakage risk point leakage model of the rapid simulation analysis model, calculate the inflow rate, and the calculated inflow rate includes the dynamic flow rate during the dynamic closing process of the gate or blade and the steady-state flow rate after the gate or blade is completely closed. S5: Based on the mass conservation equation and momentum conservation equation, the time step algorithm is used to simulate the entire process from initial leakage to complete flooding, and output the predicted simulation results, including water level-time curves, flooding isochrones, and flow velocity vector fields.

2. The rapid simulation and prediction method for flooding faults in underground powerhouses of hydropower stations according to claim 1, characterized in that, The geometric parameters include the geometric structure parameters of the factory space and the dimensions of the connecting openings, including the dimensions of doorways, pipes, or shafts.

3. The rapid simulation and prediction method for flooding faults in underground powerhouses of hydropower stations according to claim 1, characterized in that, The hydraulic parameters include a roughness coefficient and a local loss coefficient. The roughness coefficient is determined based on the surface material and the local loss coefficient is calculated based on the gate groove, sudden expansion or sudden contraction structure.

4. The rapid simulation and prediction method for flooding faults in underground powerhouses of hydropower stations according to claim 1, characterized in that, The disaster parameters include the time history of external water infiltration flow, the area of ​​the burst pipe opening, and the effective head.

5. The rapid simulation and prediction method for flooding faults in underground powerhouses of hydropower stations according to claim 1, characterized in that, In step S3, the drainage capacity calculation of the drainage system also includes dividing the collection well into a separate water storage tank and simulating the water level change of the collection well to determine the drainage flow rate.

6. The rapid simulation and prediction method for flooding faults in underground powerhouses of hydropower stations according to claim 1, characterized in that, In step S4, the leakage risk point leakage model calculates the dynamic closing process and steady-state process of the inflow based on the gate status and outflow conditions. The dynamic closing process considers the pressure of the upstream reservoir or downstream river, and the steady-state process considers the water accumulated in the water diversion tunnel or tailrace tunnel as the water source.

7. The rapid simulation and prediction method for flooding faults in underground powerhouses of hydropower stations according to claim 1, characterized in that, The time-stepping algorithm simulates with second-level precision and outputs information on the rise in water level over time, the inundation range, and the preferred path of water flow.

8. A rapid simulation and prediction system for flooding faults in underground powerhouses of hydropower stations, characterized in that: include: The construction module is used to build a rapid simulation analysis model. The parameter system of the rapid simulation analysis model includes geometric parameters, hydraulic parameters, and disaster parameters. The geometric parameters are used to describe the structural characteristics of the plant space, the hydraulic parameters are used to reflect the flow energy dissipation characteristics, and the disaster parameters are used to characterize the time-varying input of disaster triggering conditions. The reservoir module is used to divide the underground powerhouse space of the hydropower station into multiple reservoirs based on the reservoir principle and the rapid simulation analysis model, and to establish a water balance equation for each reservoir to simulate water level changes and water circulation between reservoirs. The drainage module is used to calculate the drainage capacity of the drainage system in the rapid simulation analysis model, including determining the drainage flow rate based on the pump response curve, and considering the phased drainage scheme and mobile drainage equipment. The leakage module is used to establish the leakage risk point seepage model of the rapid simulation analysis model and calculate the inflow rate. The calculated inflow rate includes the dynamic flow rate during the dynamic closing process of the gate or blade and the steady-state flow rate after the gate or blade is completely closed. The simulation module is used to simulate the entire process from initial leakage to complete flooding based on the mass conservation equation and momentum conservation equation using a time-stepping algorithm, and outputs predicted simulation results, including water level-time curves, flooding isochrones, and flow velocity vector fields.

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