Hydraulic engineering full life cycle management method and system based on digital twinning

Abstract

The invention relates to the technical field of hydraulic engineering full-life-cycle management, in particular to a hydraulic engineering full-life-cycle management method and system based on digital twinning. The method comprises the following steps: acquiring reservoir peripheral data, designing a reservoir dam based on the data, and constructing a three-dimensional model of the reservoir dam; and carrying out reservoir soil condition collection and water fluidity change estimation so as to analyze the soil settlement condition. According to the water fluidity change data and the soil settlement data, calculating water pressure distribution, foundation settlement and reservoir capacity attenuation of the dam; evaluating the efficiency attenuation of the dam generator set, optimizing the dam design, and ensuring the feasibility and efficiency of the design; according to the method, the water conservancy project full-life-cycle management technology is optimized, so that the water conservancy project design is safer and more stable.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy project full life cycle management, and in particular to a water conservancy project full life cycle management method based on digital twins. Background Art

[0002] With the rapid development of information technology, especially the advancement of digitalization and network technology, water conservancy project management has gradually introduced advanced tools such as computer-aided design (CAD), geographic information system (GIS) and automated monitoring system. These technologies have improved the problems existing in traditional management methods to a certain extent, making the design, construction and operation management of water conservancy projects more efficient and accurate. However, most of these technologies are still in a state of independent operation, lacking systematic and holistic integrated applications. In recent years, the rise of digital twin technology has provided a new solution for the full life cycle management of water conservancy projects. Digital twin technology realizes real-time monitoring, simulation and optimization of actual projects by building a virtual model of physical entities. Digital twins can not only integrate multiple data sources, but also provide more comprehensive decision support through real-time data updates and simulation predictions. The development of this technology marks that water conservancy project management has entered a new intelligent stage. However, the traditional full life cycle management method of water conservancy projects has the problems of inaccurate estimation of reservoir dam attenuation and inaccurate analysis of reservoir changes. Summary of the invention

[0003] Based on this, it is necessary to provide a full life cycle management method and system for water conservancy projects based on digital twins to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a water conservancy project life cycle management method based on digital twin is provided, and the method comprises the following steps: Step S1: Acquire data around the reservoir; design the reservoir dam according to the data around the reservoir to obtain the reservoir dam design data; construct a three-dimensional model of the reservoir dam according to the reservoir dam design data to obtain the three-dimensional model of the reservoir dam; Step S2: collecting reservoir soil conditions according to reservoir surrounding data to obtain reservoir surrounding soil condition data; using the reservoir dam three-dimensional model to estimate the change of reservoir water body fluidity to obtain reservoir water body fluidity change data; performing reservoir surrounding soil settlement analysis on the reservoir dam three-dimensional model according to the reservoir water body fluidity change data and the reservoir surrounding soil condition data to obtain the reservoir surrounding soil settlement data; Step S3: Calculate the dam water pressure distribution on the three-dimensional model of the reservoir dam according to the reservoir water body fluidity change data to obtain the dam water body pressure distribution data; simulate the dam foundation heterogeneous settlement on the three-dimensional model of the reservoir dam according to the soil settlement data around the reservoir to obtain the dam foundation heterogeneous settlement data; calculate the reservoir capacity attenuation on the three-dimensional model of the reservoir dam according to the dam foundation heterogeneous settlement data and the dam water body pressure distribution data to obtain the reservoir capacity attenuation data; Step S4: Calculate the efficiency attenuation of the dam generator set according to the reservoir capacity attenuation data to obtain the efficiency attenuation data of the dam generator set; optimize the reservoir dam design of the reservoir dam three-dimensional model according to the dam generator set efficiency attenuation data and the reservoir capacity attenuation data to obtain the reservoir dam design optimization data.

[0005] By acquiring data around the reservoir and designing the reservoir dam, the present invention can ensure that the design of the dam takes into account key factors such as topography, geology and water level, thereby formulating a scientific and reasonable dam design plan. The results of this stage have laid a solid foundation for the subsequent construction of the three-dimensional model, so that more accurate and detailed data can be used for analysis and optimization in the subsequent stage. Secondly, the collection of reservoir soil conditions and the estimation of water body fluidity changes can reveal the actual situation of the soil and the dynamic behavior of the water body, and these data are important for evaluating the soil settlement around the reservoir. Through this analysis, potential soil settlement problems can be identified and adjusted in time, reducing the structural risks caused by soil settlement and ensuring the stability and safety of the dam. When calculating the water pressure distribution of the dam, the pressure changes on each part of the dam can be accurately predicted, so as to make necessary adjustments to the design of the dam and improve its bearing capacity. At the same time, the simulation of heterogeneous foundation settlement helps to identify and solve the foundation settlement problem, thereby optimizing the dam structure design and extending the service life of the dam. By calculating the reservoir capacity decay, the capacity loss problem faced by the dam in the long-term operation process can be evaluated, providing a basis for maintenance and improvement. Finally, the calculation of the generator set efficiency attenuation based on the reservoir capacity attenuation data can foresee the performance decline trend of the generator set, and adjust and optimize the design scheme accordingly. This process not only improves the power generation efficiency of the dam. At the same time, by optimizing the design of the reservoir dam, it is possible to effectively cope with the challenges brought by capacity attenuation, achieve rational utilization of resources and long-term stable operation of the project. Therefore, the present invention is an optimization of a traditional water conservancy project full life cycle management method based on digital twins, which solves the problems of inaccurate estimation of reservoir dam attenuation and inaccurate analysis of reservoir change conditions in a traditional water conservancy project full life cycle management method based on digital twins, and improves the reservoir dam attenuation estimation capability and the accuracy of reservoir change conditions.

[0006] Preferably, step S1 comprises the following steps: Step S11: Acquire data around the reservoir; Step S12: Analyze the water resource demand of the data around the reservoir based on the digital twin to obtain the water resource demand data around the reservoir; Step S13: Designing the reservoir dam according to the reservoir water resource demand data and the reservoir surrounding data to obtain the reservoir dam design data; Step S14: constructing a three-dimensional model of the reservoir dam according to the reservoir dam design data to obtain a three-dimensional model of the reservoir dam.

[0007] By acquiring data around the reservoir, the present invention can understand in detail the environmental characteristics of the reservoir location, including basic information such as topography, geology, and climate, which provides basic data support for subsequent analysis and design. Next, based on the digital twin, the water resource demand analysis of the data around the reservoir can accurately identify and predict the actual demand for water resources in the surrounding areas of the reservoir. This process not only takes into account seasonal changes and future demand trends, but also integrates real-time data, laying a solid foundation for the scientific management and optimal allocation of water resources. After completing the water resource demand analysis, the reservoir dam is designed based on these data to ensure that the scale, type, and function of the dam meet actual needs. This design method can effectively avoid the waste of resources and dysfunction caused by excessive or insufficient design, and improve the rationality and practicality of the reservoir dam design. Next, a three-dimensional model is constructed using the dam design data, so that the design scheme can be fully displayed on the visualization platform. This not only improves the intuitiveness of the design, but also facilitates detailed analysis and optimization, helping the design team to better understand and evaluate the structural characteristics and potential problems of the dam. Overall, this series of steps achieves accurate management and effective decision-making of reservoir projects by combining data acquisition, demand analysis, design optimization and 3D modeling. By comprehensively utilizing digital twin technology and 3D models, these steps significantly improve the scientificity and accuracy of the design, helping to reduce risks and improve efficiency in actual construction.

[0008] Preferably, step S13 comprises the following steps: Step S131: Obtain historical rainfall data around the reservoir; Step S132: extracting the terrain around the reservoir based on the data around the reservoir to obtain the terrain data around the reservoir; Step S133: collecting surrounding geological conditions according to the terrain data around the reservoir to obtain geological condition data around the reservoir; Step S134: Calculate the water storage volume of the reservoir according to the water resource demand data around the reservoir to obtain the water storage volume data of the reservoir; Step S135: Count the historical maximum rainfall according to the historical rainfall data around the reservoir to obtain the historical maximum rainfall data around the reservoir; Step S136: predicting the highest point that the water level can reach based on the reservoir water storage volume data, the historical maximum rainfall data around the reservoir, and the terrain data around the reservoir to obtain the predicted data of the highest point that the water level can reach; Step S137: Design the reservoir dam according to the prediction data of the highest point that the water level can reach, the terrain data around the reservoir, and the geological condition data around the reservoir to obtain the reservoir dam design data.

[0009] The present invention obtains historical rainfall data around the reservoir, provides an in-depth understanding of rainfall patterns and rainfall distribution, and lays a data foundation for water resources management and dam design. By analyzing these historical data, seasonal fluctuations in rainfall and the frequency of extreme weather events can be identified, providing strong support for flood control design and capacity planning of reservoirs. Terrain extraction based on data around the reservoir can accurately depict the terrain characteristics around the reservoir, which is of great significance for subsequent geological condition collection and dam design. Understanding terrain characteristics helps to evaluate the flow path, water accumulation area and its impact on the surrounding environment, ensuring the rationality of the design scheme. The collection of geological conditions further enhances the understanding of the geological conditions in the reservoir construction area. By obtaining geological condition data, the stability of the foundation, soil type and potential geological risks can be evaluated, which is crucial for designing a stable and reliable dam structure. Calculating the water storage volume based on water resource demand data helps to determine the reasonable volume and water storage capacity of the reservoir, thereby meeting the regional water resource demand and optimizing the use efficiency of the reservoir. This calculation ensures that the reservoir can operate effectively under different demand scenarios and avoids waste or shortage of resources. Statistics on the historical maximum rainfall provide a quantitative analysis of extreme rainfall events and help predict reservoir operations under extreme meteorological conditions. This prediction can guide the design of flood control measures and emergency response plans to reduce the risks caused by extreme weather. By combining water storage volume data, historical maximum rainfall data and terrain data, it is possible to predict the highest point where the water level can reach, which is crucial for evaluating the performance of reservoirs at different water levels. Ultimately, the design of reservoir dams based on comprehensive forecast data, terrain and geological conditions can ensure the safety and effectiveness of the dam structure.

[0010] Preferably, designing a reservoir dam based on the predicted data of the highest water level point, the terrain data around the reservoir, and the geological data around the reservoir includes the following steps: Calculate the height of the reservoir dam based on the predicted data of the highest point that the water level can reach and the terrain data around the reservoir to obtain the height data of the reservoir dam; The water depth pressure at the lowest water level of the reservoir is calculated based on the reservoir dam height data and the predicted data of the highest water level point, and the water depth pressure data at the lowest water level of the reservoir is obtained; According to the water depth pressure data at the lowest water level of the reservoir, the geological condition data around the reservoir are used to extract the stable geological water pressure bearing area, and the geological water pressure bearing stable area data is obtained; The site selection data for reservoir dam construction is obtained by using the regional data of geological water pressure bearing stability and the terrain data around the reservoir to perform site intersection operations; Conduct reservoir water velocity test based on reservoir dam construction site selection data to obtain reservoir dam construction site selection water velocity data; The dam thickness data is calculated based on the water depth pressure data at the lowest water level of the reservoir and the water flow velocity data of the reservoir dam construction site selection to obtain the reservoir dam thickness data; The reservoir dam is designed using the reservoir dam height data, reservoir dam thickness data and reservoir dam construction site selection data to obtain the reservoir dam design data.

[0011] The present invention calculates the dam height by using the predicted data of the highest point that the water level can reach and the terrain data around the reservoir, and can accurately determine the necessary height of the dam to ensure that the dam can accommodate the maximum water level under extreme weather. This calculation provides key parameters for the design, avoids overflow or structural problems caused by improper design, and ensures the safety and stability of the reservoir at different water levels. After determining the dam height, the water depth pressure data at the lowest water level of the reservoir is calculated, and the pressure borne by the dam under the lowest water level can be deeply understood. This data is crucial for evaluating the pressure resistance and stability of the dam structure, ensuring that the dam can safely bear the pressure of the water body under water level fluctuations and extreme conditions. According to the water depth pressure data at the lowest water level, the extraction of the geological water pressure bearing stable area can identify the geological stable area under high water pressure conditions. This analysis helps determine the geological area suitable for dam construction, avoids building dams in areas with insufficient geological bearing capacity, and thus improves the long-term stability and safety of the dam. Using the geological water pressure bearing stable area data and terrain data to perform site intersection operations, the dam construction site that meets the geological and terrain requirements can be accurately found. This process ensures that the dam is constructed in the best geographical location, thereby reducing risks during construction and operation and improving the overall benefits of the project. After the construction location is selected, water flow velocity testing can obtain water flow velocity data at that location, which is crucial for understanding the water flow conditions in the reservoir and its surroundings. Accurate flow velocity data helps optimize the dam design and ensure the stability and efficiency of the dam under changing flow rates. The dam thickness calculation combined with water depth pressure data and water flow velocity data of the construction site can ensure that the dam thickness meets the bearing requirements, while considering the impact of flow velocity on the dam structure in the design. This calculation helps to design a dam that is both strong and efficient, ensuring its safety and reliability in actual use. Finally, the dam design based on the height, thickness and construction site data provides a comprehensive design solution to ensure the optimization of the dam in function and structure. This series of steps not only improves the scientificity and accuracy of the design, but also enhances the overall safety of the project.

[0012] Preferably, step S2 comprises the following steps: Step S21: collecting soil condition data of the reservoir according to the data of the reservoir surrounding area to obtain soil condition data of the reservoir surrounding area; Step S22: analyzing the critical flow velocity of soil water flow on the soil condition data around the reservoir based on the digital twin to obtain the critical flow velocity data of the surrounding soil water flow; Step S23: using the three-dimensional model of the reservoir dam to estimate the change of reservoir water body fluidity, and obtain reservoir water body fluidity change data; Step S24: analyzing soil settlement around the reservoir based on the reservoir water body fluidity change data and the surrounding soil water flow critical velocity data to obtain soil settlement data around the reservoir.

[0013] By collecting soil condition data around the reservoir, the present invention can deeply understand the properties of the soil, including its composition, moisture, density, etc., which provides basic data for subsequent soil analysis and dam design. Understanding the soil condition helps to evaluate the bearing capacity and stability of the soil, thereby avoiding structural problems caused by unsuitable soil conditions. Based on the digital twin technology, the critical velocity of soil water flow is analyzed for these soil condition data, and the critical velocity of the soil under different water flow conditions can be accurately calculated. This analysis helps to identify the stability of the soil under different water flow intensities and predict potential risks of soil erosion or loss, so as to formulate corresponding protective measures to protect the reservoir and its surrounding environment. Then, the three-dimensional model of the reservoir dam is used to estimate the change of water body fluidity, and the dynamic behavior of the water flow in the reservoir can be understood in detail, including changes in flow velocity, flow direction and flow. These data are crucial for evaluating the water management and regulation strategy of the reservoir, and can help optimize the flow design of the water body and reduce the impact of the water body on the dam and its surrounding environment. At the same time, these fluidity change data provide necessary information for soil settlement analysis, making the analysis results more accurate and reliable. The soil settlement analysis, combined with the reservoir water flow change data and the soil water flow critical velocity data, can provide a deep understanding of the settlement of the surrounding soil under the influence of water flow changes. This analysis reveals the specific impact of water flow on soil settlement, so that soil settlement problems that occur during dam construction and operation can be predicted and evaluated. By understanding the soil settlement, necessary engineering measures can be taken, such as strengthening the foundation or adjusting the design, to ensure the stability and safety of the dam and its surrounding areas.

[0014] Preferably, step S24 comprises the following steps: Step S241: Calculate the change of water flow rate according to the change data of water body fluidity of the reservoir to obtain the change data of water flow rate of the reservoir; Step S242: Calculating the water flow impact pressure on the soil around the reservoir according to the reservoir water flow velocity change data to obtain water flow impact pressure data; Step S243: simulating the surrounding soil water flow erosion based on the water flow impact pressure data and the reservoir water flow velocity change data on the surrounding soil water flow critical velocity data to obtain the soil water flow erosion data around the reservoir; Step S244: analyzing soil particles transported by water flow according to the soil water erosion data around the reservoir to obtain soil particle data transported by water flow in the reservoir; Step S245: Perform soil settlement analysis around the reservoir based on the soil particle data transported by reservoir water flow and the soil water erosion data around the reservoir to obtain soil settlement data around the reservoir.

[0015] The present invention can accurately grasp the changing trend of water velocity by calculating the change of water velocity based on the change data of water body fluidity in the reservoir. These data are crucial to understanding the dynamic changes of water body flow, and help to identify and predict the potential impact of water velocity fluctuations on the reservoir and its surrounding areas. This calculation provides a detailed understanding of water flow behavior and provides a reliable basis for subsequent impact pressure analysis and soil erosion simulation. The calculation of water flow impact pressure using water flow velocity change data can reveal the actual impact force of water flow on soil. These impact pressure data provide quantitative indicators for analyzing the impact of water flow on soil, which helps to evaluate the potential threat of water flow to soil stability. By understanding the distribution of impact pressure, effective measures can be formulated to reduce or prevent the negative impact of water flow on surrounding soil. Water flow erosion simulation based on water flow impact pressure data and water flow velocity change data on the critical velocity data of surrounding soil water flow can simulate and predict in detail the erosion of water flow on soil under different conditions. This simulation result helps identify high-risk areas for soil erosion and provides a scientific basis for taking protective measures. By understanding the erosion behavior of soil under various water flow conditions, soil loss and environmental degradation in the reservoir area can be effectively reduced. Water transport soil particle analysis based on water erosion data can quantify the transport of soil particles by water. This analysis helps to understand the distribution and migration patterns of soil particles in water flow, thereby evaluating soil stability and loss. Soil settlement analysis based on water transport soil particle data and soil erosion data can comprehensively evaluate the settlement of soil under the action of water flow. This analysis provides data support for identifying and solving settlement problems, helping to optimize reservoir design and maintenance strategies and ensure the long-term stability of dams and their surrounding areas.

[0016] Preferably, step S3 comprises the following steps: Step S31: Calculate the water level rise of the reservoir dam three-dimensional model according to the reservoir water body fluidity change data to obtain the reservoir water body water level rise data; Step S32: Calculating the dam water pressure distribution on the reservoir dam three-dimensional model according to the reservoir water level rise data to obtain the dam water pressure distribution data; Step S33: simulating heterogeneous settlement of the dam foundation on the three-dimensional model of the reservoir dam according to the soil settlement data around the reservoir to obtain heterogeneous settlement data of the dam foundation; Step S34: analyzing the internal stress distribution of the dam according to the heterogeneous settlement data of the dam foundation and the water pressure distribution data of the dam to obtain the internal stress distribution data of the dam; Step S35: performing a dam crack risk assessment based on the dam internal stress distribution data to obtain dam crack risk assessment data; Step S36: Calculate the water tightness of the dam according to the dam crack risk assessment data and the reservoir water body fluidity change data to obtain the reservoir dam water tightness data; Step S37: Calculate the reservoir capacity attenuation on the three-dimensional model of the reservoir dam according to the reservoir dam water tightness data and the dam crack risk assessment data to obtain the reservoir capacity attenuation data.

[0017] The present invention can accurately predict the change of reservoir water level under different flow conditions by calculating the water level rise based on the data of the change of reservoir water body fluidity. This prediction helps to evaluate the water level fluctuation of the dam in actual operation, ensure that the design can adapt to extreme weather and water flow conditions, and avoid overflow or structural problems caused by excessive water level. According to the water level rise data, the water pressure distribution of the dam is calculated, and the pressure on each part of the dam under different water levels can be clearly understood. This data helps to optimize the dam design, ensure that the dam can evenly distribute and withstand pressure under various water level conditions, and improve the stability and safety of the dam. According to the soil settlement data, the heterogeneous settlement simulation of the dam foundation can evaluate the performance of the foundation under different settlement conditions. This analysis helps to identify the uneven settlement problem of the dam foundation, and provides an improvement basis for the dam design and construction to reduce the structural risks caused by foundation settlement. The internal stress distribution analysis of the dam based on the heterogeneous settlement data and pressure distribution data can provide a detailed understanding of the stress state inside the dam. This data is crucial for assessing the overall stability and strength of the dam structure, helping to identify potential stress concentration areas and make necessary structural reinforcement or adjustments. Crack risk assessment based on internal stress distribution data can identify the risk of cracks in the dam structure. This assessment helps prevent and control the occurrence of cracks, thereby avoiding leakage and structural failure caused by cracks and ensuring the long-term safety and reliability of the dam. Combining crack risk assessment data with watertightness calculations, the watertightness of the dam can be accurately assessed. This data helps ensure that the dam can effectively prevent leakage and protect the water resources of the reservoir during long-term use. Through watertightness data and capacity decay calculations, it is possible to understand the changes in reservoir capacity under different operating conditions, adjust management strategies in a timely manner, ensure the effective capacity and function of the reservoir, and optimize resource utilization.

[0018] Preferably, step S36 includes the following steps: Step S361: performing a reservoir dam rupture simulation on the reservoir dam three-dimensional model according to the dam crack risk assessment data to obtain reservoir dam rupture data; Step S362: Obtaining reservoir dam rupture complexity data and reservoir rupture length data according to the rupture complexity analysis and rupture length measurement of the reservoir dam rupture data; Step S363: performing dam seepage path analysis according to the reservoir dam rupture complexity data and the reservoir rupture length data to obtain reservoir dam rupture seepage path data; Step S364: estimating the reservoir dam seepage flow rate according to the reservoir dam rupture seepage flow path data and the reservoir water body fluidity change data to obtain the reservoir dam water seepage flow rate data; Step S365: Calculate the water tightness of the dam based on the water seepage volume data of the reservoir dam and the seepage path data of the reservoir dam rupture to obtain the water tightness data of the reservoir dam.

[0019] The present invention can deeply understand the rupture behavior of the dam in the event of cracks by simulating the rupture of the reservoir dam based on the dam crack risk assessment data. This simulation can predict potential rupture modes and crack expansion trends, thereby evaluating the stability and risk of the dam under different rupture conditions. This forward-looking analysis helps to discover and solve problems in a timely manner and enhance the safety of the dam. Rupture complexity analysis and rupture length measurement can provide a detailed understanding of the nature and scale of the rupture. These data help determine the severity and impact range of the cracks, so that dam design and maintenance can be optimized for specific risk points. The dam seepage path analysis based on the rupture complexity data and rupture length data can clarify the flow path of water in the rupture area. This analysis helps to identify the seepage characteristics and paths in the rupture area, thereby providing a basis for preventing and controlling leakage and ensuring that the dam can effectively deal with the water flow problems caused by the rupture. The reservoir dam seepage volume estimation based on the seepage path data and water body fluidity change data can accurately predict the dam seepage volume under different rupture conditions. This prediction provides data support for assessing the impact of seepage on dam stability and reservoir management, and helps to formulate corresponding response strategies. The dam water tightness calculation based on water seepage volume data and seepage path data can comprehensively evaluate the dam's waterproof ability under actual operating conditions. This calculation ensures that the dam can effectively prevent water leakage, thereby protecting the effective capacity of the reservoir and the safety of the dam structure.

[0020] Preferably, step S4 comprises the following steps: Step S41: analyzing the reservoir dam inflow flow rate according to the reservoir capacity attenuation data to obtain the reservoir dam inflow flow rate data; Step S42: Calculate the efficiency attenuation of the dam generator set according to the water inflow data of the reservoir dam to obtain the efficiency attenuation data of the dam generator set; Step S43: conducting a dam design feasibility assessment on the reservoir dam design data according to the dam generator set efficiency attenuation data, the reservoir capacity attenuation data, and the soil settlement data around the reservoir, to obtain the reservoir dam design feasibility data; Step S44: optimizing the reservoir dam design on the reservoir dam three-dimensional model according to the reservoir dam construction feasibility data and the dam generator efficiency attenuation data to obtain reservoir dam design optimization data.

[0021] The present invention can accurately calculate the actual inflow flow of the reservoir dam by analyzing the inflow flow of the reservoir capacity decay data. This data provides basic information for evaluating the inflow capacity of the reservoir under different capacity conditions, helps to understand the inflow status and change trend of the reservoir, thereby optimizing the management and operation strategy of the reservoir and ensuring that the reservoir can operate effectively under different water level conditions. The efficiency decay calculation of the dam generator set based on the inflow flow data can quantify the efficiency change of the generator set under different flow conditions. This calculation helps to identify the degree of performance degradation of the generator set when the water volume decreases, thereby providing data support for adjusting the power generation strategy and improving the power generation efficiency. The feasibility of the dam design is evaluated based on the generator set efficiency decay data, the reservoir capacity decay data and the soil settlement data, and the feasibility of the design scheme under actual operating conditions can be comprehensively analyzed. This evaluation comprehensively considers the capacity decay, efficiency change and settlement issues. The design optimization of the three-dimensional model of the reservoir dam based on the design feasibility data and the generator set efficiency decay data can effectively adjust and improve the dam design scheme. This optimization process ensures that the design can meet the challenges in actual operation, improve the performance and reliability of the dam, and maximize the power generation efficiency and the overall function of the reservoir. It can achieve scientific optimization of reservoir dam design to ensure its optimal performance and long-term stability under different operating conditions.

[0022] Preferably, the present invention also provides a water conservancy project life cycle management system based on digital twins, which is used to execute the water conservancy project life cycle management method. The water conservancy project life cycle management system includes: The reservoir dam three-dimensional model construction module obtains the data around the reservoir; designs the reservoir dam according to the data around the reservoir to obtain the reservoir dam design data; constructs the reservoir dam three-dimensional model according to the reservoir dam design data to obtain the reservoir dam three-dimensional model; The soil settlement analysis module around the reservoir collects the soil condition of the reservoir based on the data around the reservoir to obtain the soil condition data around the reservoir; uses the three-dimensional model of the reservoir dam to estimate the change of the fluidity of the reservoir water body and obtain the data of the change of the fluidity of the reservoir water body; analyzes the soil settlement around the reservoir based on the data of the change of the fluidity of the reservoir water body and the three-dimensional model of the reservoir dam to obtain the soil settlement data around the reservoir; The reservoir capacity attenuation calculation module calculates the dam water pressure distribution of the three-dimensional model of the reservoir dam according to the reservoir water body fluidity change data, and obtains the dam water body pressure distribution data; simulates the dam foundation heterogeneous settlement of the three-dimensional model of the reservoir dam according to the soil settlement data around the reservoir, and obtains the dam foundation heterogeneous settlement data; calculates the reservoir capacity attenuation of the three-dimensional model of the reservoir dam according to the dam foundation heterogeneous settlement data and the dam water body pressure distribution data, and obtains the reservoir capacity attenuation data; The reservoir dam design optimization module calculates the efficiency attenuation of the dam generator set according to the reservoir capacity attenuation data to obtain the efficiency attenuation data of the dam generator set; it optimizes the reservoir dam design of the three-dimensional model of the reservoir dam according to the efficiency attenuation data of the dam generator set to obtain the reservoir dam design optimization data.

[0023] The present invention has a beneficial effect. By acquiring data around the reservoir and designing the reservoir dam, the present invention can ensure that the design of the dam takes into account key factors such as topography, geology and water level, thereby formulating a scientific and reasonable dam design plan. The results of this stage have laid a solid foundation for the subsequent construction of the three-dimensional model, so that more accurate and detailed data can be used for analysis and optimization in the subsequent stage. Secondly, the collection of reservoir soil conditions and the estimation of water body fluidity changes can reveal the actual situation of the soil and the dynamic behavior of the water body. These data are important for evaluating the soil settlement around the reservoir. Through this analysis, potential soil settlement problems can be identified and adjusted in time, reducing the structural risks caused by soil settlement and ensuring the stability and safety of the dam. When calculating the water pressure distribution of the dam, the pressure changes on each part of the dam can be accurately predicted, so as to make necessary adjustments to the design of the dam and improve its bearing capacity. At the same time, the simulation of heterogeneous foundation settlement helps to identify and solve the foundation settlement problem, thereby optimizing the dam structure design and extending the service life of the dam. By calculating the attenuation of reservoir capacity, it is possible to evaluate the capacity loss problem faced by the dam during long-term operation, providing a basis for maintenance and improvement. Finally, the calculation of the efficiency attenuation of the generator set based on the reservoir capacity attenuation data can foresee the performance decline trend of the generator set, and adjust and optimize the design scheme accordingly. This process not only improves the power generation efficiency of the dam. At the same time, by optimizing the design of the reservoir dam, it is possible to effectively cope with the challenges brought by capacity attenuation, achieve rational utilization of resources and long-term stable operation of the project. Therefore, the present invention is an optimization of a traditional full life cycle management method for water conservancy projects based on digital twins, which solves the problems of inaccurate estimation of reservoir dam attenuation and inaccurate analysis of reservoir change conditions in a traditional full life cycle management method for water conservancy projects based on digital twins, and improves the ability to estimate reservoir dam attenuation and the accuracy of reservoir change conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the steps of a water conservancy project life cycle management method based on digital twins; Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart; Figure 3 for Figure 1 Detailed implementation steps of step S4 in FIG.

[0025] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0026] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0027] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0028] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0029] To achieve this, please refer to Figures 1 to 3 , a water conservancy project full life cycle management method based on digital twin, the method comprising the following steps: Step S1: Acquire data around the reservoir; design the reservoir dam according to the data around the reservoir to obtain the reservoir dam design data; construct a three-dimensional model of the reservoir dam according to the reservoir dam design data to obtain the three-dimensional model of the reservoir dam; Step S2: collecting reservoir soil conditions according to reservoir surrounding data to obtain reservoir surrounding soil condition data; using the reservoir dam three-dimensional model to estimate the change of reservoir water body fluidity to obtain reservoir water body fluidity change data; performing reservoir surrounding soil settlement analysis on the reservoir dam three-dimensional model according to the reservoir water body fluidity change data and the reservoir surrounding soil condition data to obtain the reservoir surrounding soil settlement data; Step S3: Calculate the dam water pressure distribution on the three-dimensional model of the reservoir dam according to the reservoir water body fluidity change data to obtain the dam water body pressure distribution data; simulate the dam foundation heterogeneous settlement on the three-dimensional model of the reservoir dam according to the soil settlement data around the reservoir to obtain the dam foundation heterogeneous settlement data; calculate the reservoir capacity attenuation on the three-dimensional model of the reservoir dam according to the dam foundation heterogeneous settlement data and the dam water body pressure distribution data to obtain the reservoir capacity attenuation data; Step S4: Calculate the efficiency attenuation of the dam generator set according to the reservoir capacity attenuation data to obtain the efficiency attenuation data of the dam generator set; optimize the reservoir dam design of the reservoir dam three-dimensional model according to the dam generator set efficiency attenuation data and the reservoir capacity attenuation data to obtain the reservoir dam design optimization data.

[0030] In the embodiment of the present invention, reference Figure 1 The above is a schematic diagram of the steps of a water conservancy project life cycle management method based on digital twins of the present invention. In this example, the water conservancy project life cycle management method based on digital twins includes the following steps: Step S1: Acquire data around the reservoir; design the reservoir dam according to the data around the reservoir to obtain the reservoir dam design data; construct a three-dimensional model of the reservoir dam according to the reservoir dam design data to obtain the three-dimensional model of the reservoir dam; In an embodiment of the present invention, the data obtained around the reservoir include topography, climate, rainfall, soil type and its physical properties, etc. Geographic Information System (GIS) tools and remote sensing technology are used for data collection and processing. Topographic data can be obtained through digital elevation model (DEM), while climate and rainfall data can be extracted from meteorological monitoring stations and meteorological databases. The acquired surrounding data are comprehensively analyzed by data analysis tools to identify the geological structure and water resource conditions of the area around the reservoir. Subsequently, based on these data, the preliminary design of the reservoir dam is carried out, taking into account the requirements of the dam's size, material, and structural strength. After the design is completed, a three-dimensional model of the dam is constructed using computer-aided design (CAD) software, which shows in detail the geometry of the dam, structural components, and relationship with the surrounding environment to ensure the accuracy and feasibility of the design.

[0031] Step S2: collecting reservoir soil conditions according to reservoir surrounding data to obtain reservoir surrounding soil condition data; using the reservoir dam three-dimensional model to estimate the change of reservoir water body fluidity to obtain reservoir water body fluidity change data; performing reservoir surrounding soil settlement analysis on the reservoir dam three-dimensional model according to the reservoir water body fluidity change data and the reservoir surrounding soil condition data to obtain the reservoir surrounding soil settlement data; In an embodiment of the present invention, soil conditions are collected around the reservoir, and soil samples are collected at different locations and depths using a soil sampler. The collected soil samples are subjected to laboratory analysis to test physical properties such as soil density, water content, shear strength, and compressibility. Combined with these soil attribute data, numerical analysis tools are used to estimate the fluidity of the reservoir water body. The flow pattern of the water body under different operating conditions, including flow velocity, flow direction, and influx, is calculated using a fluid mechanics model. Combined with the fluidity change data and soil condition data, a settlement analysis method is applied to predict the settlement of the soil around the reservoir under different water flow conditions.

[0032] Step S3: Calculate the dam water pressure distribution on the three-dimensional model of the reservoir dam according to the reservoir water body fluidity change data to obtain the dam water body pressure distribution data; simulate the dam foundation heterogeneous settlement on the three-dimensional model of the reservoir dam according to the soil settlement data around the reservoir to obtain the dam foundation heterogeneous settlement data; calculate the reservoir capacity attenuation on the three-dimensional model of the reservoir dam according to the dam foundation heterogeneous settlement data and the dam water body pressure distribution data to obtain the reservoir capacity attenuation data; In the embodiment of the present invention, the water pressure distribution on the dam surface is calculated using fluid dynamics formulas based on the reservoir water flow change data. The calculation takes into account water level changes, flow velocity changes, and the dynamic characteristics of the water body to determine the pressure distribution of the dam under different water level conditions. Subsequently, based on the surrounding soil settlement data, the dam foundation is simulated for heterogeneous settlement using a geomechanical model. This process includes detailed modeling of the settlement characteristics of the soil layer to predict the impact of uneven settlement on the dam foundation. Next, the reservoir capacity attenuation calculation is performed in combination with the dam water pressure distribution and foundation settlement data.

[0033] Step S4: Calculate the efficiency attenuation of the dam generator set according to the reservoir capacity attenuation data to obtain the efficiency attenuation data of the dam generator set; optimize the reservoir dam design of the reservoir dam three-dimensional model according to the dam generator set efficiency attenuation data and the reservoir capacity attenuation data to obtain the reservoir dam design optimization data.

[0034] In the embodiment of the present invention, the efficiency decay of the dam generator set is calculated using the reservoir capacity decay data. This calculation adjusts the flow and pressure changes of the generator set according to the capacity decay, thereby obtaining the efficiency decay data under actual operating conditions. Then, the design optimization is performed based on the efficiency decay data of the dam generator set and the reservoir capacity decay data in combination with the three-dimensional model of the reservoir dam. This optimization process includes adjusting the dam design parameters to improve the power generation efficiency and optimize the reservoir capacity.

[0035] Preferably, step S1 comprises the following steps: Step S11: Acquire data around the reservoir; Step S12: Analyze the water resource demand of the data around the reservoir based on the digital twin to obtain the water resource demand data around the reservoir; Step S13: Designing the reservoir dam according to the reservoir water resource demand data and the reservoir surrounding data to obtain the reservoir dam design data; Step S14: constructing a three-dimensional model of the reservoir dam according to the reservoir dam design data to obtain a three-dimensional model of the reservoir dam.

[0036] In the embodiment of the present invention, the terrain, climate, rainfall, soil and geological data around the reservoir are collected. These data are obtained through field surveys and remote sensing technology, and the data are integrated using a geographic information system (GIS). The terrain data is obtained through a digital elevation model (DEM), the climate and rainfall data are extracted from a meteorological station and a meteorological database, and the soil and geological data are obtained through soil sampling and geological drilling. Based on the acquired data around the reservoir, the digital twin technology is used to analyze the water resource demand. By establishing a water resource demand model, the actual meteorological data, historical water use records and forecast data are input into the model. The digital twin technology simulates the consumption and demand changes of water resources in real time through a virtual model, and analyzes various water use situations, such as agricultural, industrial and domestic water demand. The analysis results generate water resource demand data, including the demand and change trend in each time period. The reservoir dam is designed based on the water resource demand data and the surrounding environment data. During the design process, the water consumption forecast in the water resource demand data is considered, and the preliminary design is carried out in combination with the terrain and geological data. This stage involves calculating the design parameters such as the height, width and material selection of the dam. Structural engineering analysis methods are used to evaluate the impact of different design parameters on dam stability and select the optimal design solution. Based on the determined reservoir dam design parameters, a three-dimensional model of the reservoir dam is constructed. The design data is input into the model using computer-aided design (CAD) tools to establish a three-dimensional geometric model of the dam. The model includes various structural components of the dam, such as spillways, dam bodies, and foundations. Detailed geometric verification of the three-dimensional model is performed to ensure that it accurately reflects the design intent and actual construction requirements.

[0037] Preferably, step S13 comprises the following steps: Step S131: Obtain historical rainfall data around the reservoir; Step S132: extracting the terrain around the reservoir based on the data around the reservoir to obtain the terrain data around the reservoir; Step S133: collecting surrounding geological conditions according to the terrain data around the reservoir to obtain geological condition data around the reservoir; Step S134: Calculate the water storage volume of the reservoir according to the water resource demand data around the reservoir to obtain the water storage volume data of the reservoir; Step S135: Count the historical maximum rainfall according to the historical rainfall data around the reservoir to obtain the historical maximum rainfall data around the reservoir; Step S136: predicting the highest point that the water level can reach based on the reservoir water storage volume data, the historical maximum rainfall data around the reservoir, and the terrain data around the reservoir to obtain the predicted data of the highest point that the water level can reach; Step S137: Design the reservoir dam according to the prediction data of the highest point that the water level can reach, the terrain data around the reservoir, and the geological condition data around the reservoir to obtain the reservoir dam design data.

[0038] In an embodiment of the present invention, historical rainfall data around the reservoir is obtained, including rainfall records for the past several years or decades. These data are obtained by accessing historical records of a meteorological data center or a meteorological station, using standard meteorological data recording methods, such as rainfall metering and recording instruments. The data includes the time distribution, intensity and frequency of rainfall. These rainfall records are organized into time series data, and statistical analysis is performed to determine the annual average, maximum, minimum and changing trends of rainfall. The terrain data around the reservoir is extracted from high-resolution satellite images or aerial images using a geographic information system (GIS) tool. Terrain extraction includes identifying features such as undulations, slopes, ridges and valleys of the surface. The elevation data of the terrain is obtained by using a digital elevation model (DEM), and terrain analysis algorithms such as slope analysis and watershed analysis are applied to extract detailed terrain features of the reservoir area. The surrounding geological conditions are collected based on the extracted terrain data. Soil and rock samples are obtained through geological exploration techniques such as drilling and sampling, and laboratory tests are performed to analyze the type, structure, bearing capacity and distribution of rock layers of the soil. The reservoir water storage volume is calculated based on the water resource demand data around the reservoir. This calculation determines the volume of water that the reservoir needs to accommodate based on the water demand forecast and flow requirements in the water resource demand data. The water resource management model simulates the water demand in different seasons and years and calculates the minimum and maximum water storage capacity of the reservoir. The historical maximum rainfall around the reservoir is counted based on historical rainfall data. This statistical process involves extreme value analysis of rainfall data to identify the maximum rainfall events that have occurred in history. Statistical methods such as extreme value theory or frequency analysis are used to calculate the statistical characteristics of maximum rainfall and predict the rainfall intensity that occurs under extreme climate conditions. The highest point that the water level can reach is predicted by combining the reservoir water storage volume data, historical maximum rainfall data and terrain data. The hydrological model is used to simulate the water level changes of the reservoir under different rainfall conditions, and the spatial distribution of the water level is predicted taking into account the influence of terrain. This process includes calculating the water level rise height and comparing it with the surrounding terrain data to determine the highest water point that the reservoir can reach, and designing the reservoir dam based on the predicted data of the highest water level, terrain data and geological conditions data. During the design process, the design height and structural strength of the dam are determined taking into account the data of the highest water level. The dam foundation is designed based on geological conditions, and appropriate materials and construction methods are selected. Through structural engineering analysis, the dam design is optimized to meet the reservoir capacity, stability and safety requirements.

[0039] Preferably, designing a reservoir dam based on the predicted data of the highest water level point, the terrain data around the reservoir, and the geological data around the reservoir includes the following steps: Calculate the height of the reservoir dam based on the predicted data of the highest point that the water level can reach and the terrain data around the reservoir to obtain the height data of the reservoir dam; The water depth pressure at the lowest water level of the reservoir is calculated based on the reservoir dam height data and the predicted data of the highest water level point, and the water depth pressure data at the lowest water level of the reservoir is obtained; According to the water depth pressure data at the lowest water level of the reservoir, the geological condition data around the reservoir are used to extract the stable geological water pressure bearing area, and the geological water pressure bearing stable area data is obtained; The site selection data for reservoir dam construction is obtained by using the regional data of geological water pressure bearing stability and the terrain data around the reservoir to perform site intersection operations; Conduct reservoir water velocity test based on reservoir dam construction site selection data to obtain reservoir dam construction site selection water velocity data; The dam thickness data is calculated based on the water depth pressure data at the lowest water level of the reservoir and the water flow velocity data of the reservoir dam construction site selection to obtain the reservoir dam thickness data; The reservoir dam is designed using the reservoir dam height data, reservoir dam thickness data and reservoir dam construction site selection data to obtain the reservoir dam design data.

[0040] In an embodiment of the present invention, the height of the reservoir dam is calculated using the predicted data of the highest point that the water level can reach and the terrain data around the reservoir, and the height that the reservoir dam needs to reach is calculated by using the digital elevation model (DEM) and the water level prediction data through the geographic information system (GIS) tool to ensure that overflow does not occur under the maximum water level. When calculating, the predicted water level is compared with the terrain undulation data to determine the minimum height of the dam. The height value will take into account the influence of water level fluctuations and the maximum water level, and the water depth pressure at the lowest water level of the reservoir is calculated based on the calculated reservoir dam height data and the predicted data of the highest point that the water level can reach. The water depth pressure at the bottom of the reservoir under the lowest water level of the reservoir is calculated by applying the fluid statics formula. This involves using the dam design height and water level data to calculate the vertical pressure and horizontal pressure exerted by the water body on the dam body. The formula used for pressure calculation is P = ρgh, where P is pressure, ρ is the density of water, g is the acceleration of gravity, and h is the water depth. According to the water pressure data at the lowest water level of the reservoir, the geological condition data around the reservoir are used to extract the stable area of ​​geological water pressure bearing. Through the geological exploration data, such as soil bearing capacity and rock layer distribution, combined with the water pressure data, the stability of soil and rock under the water pressure is analyzed. The geomechanical analysis method is used to identify the stable area under water pressure. The site intersection operation is performed using the geological water pressure bearing stability area data and the terrain data around the reservoir to obtain the reservoir dam construction site selection data. Through the geographic information system (GIS) data superposition and spatial analysis, the stable area and the terrain data are intersected. The reservoir water flow rate test is carried out according to the determined reservoir dam construction site selection data. This includes on-site water flow measurement in the selected area, and the water flow rate is monitored in real time using instruments such as flow meters. The test data includes the spatial distribution and time variation of the flow rate. The dam thickness data is calculated based on the water pressure data at the lowest water level of the reservoir and the water flow rate data of the reservoir dam construction site selection. Combined with the water flow rate test results and water pressure, the minimum thickness required for the dam is calculated to resist the impact of the water flow and the pressure generated by the water depth. The reservoir dam is designed using the reservoir dam height data, reservoir dam thickness data and reservoir dam construction site selection data. The above data are integrated and the detailed design plan of the dam is determined through the structural design specifications. Including the specific structure of the dam, material selection, construction method and durability requirements.

[0041] Preferably, step S2 comprises the following steps: Step S21: collecting soil condition data of the reservoir according to the data of the reservoir surrounding area to obtain soil condition data of the reservoir surrounding area; Step S22: analyzing the critical flow velocity of soil water flow on the soil condition data around the reservoir based on the digital twin to obtain the critical flow velocity data of the surrounding soil water flow; Step S23: using the three-dimensional model of the reservoir dam to estimate the change of reservoir water body fluidity, and obtain reservoir water body fluidity change data; Step S24: analyzing soil settlement around the reservoir based on the reservoir water body fluidity change data and the surrounding soil water flow critical velocity data to obtain soil settlement data around the reservoir.

[0042] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes: Step S21: collecting soil condition data of the reservoir according to the data of the reservoir surrounding area to obtain soil condition data of the reservoir surrounding area; In the embodiment of the present invention, drilling sampling is carried out around the reservoir, and the sampling depth covers the entire soil layer. The soil samples are sent to the laboratory for physical and chemical property analysis, including soil particle composition, porosity, moisture content, shear strength and other tests. A soil testing program is used to ensure the accuracy and reliability of the data. The soil condition data includes the bearing capacity, compressibility, liquefaction potential, etc. of the soil.

[0043] Step S22: analyzing the critical flow velocity of soil water flow on the soil condition data around the reservoir based on the digital twin to obtain the critical flow velocity data of the surrounding soil water flow; In the embodiment of the present invention, the actual soil condition data is input into the virtual model through the digital twin platform. The fluid dynamics algorithm in the model is used to simulate the response of the soil at different flow rates and determine the interaction between water flow and soil. The critical flow rate refers to the flow rate at which soil particles begin to move due to the impact of water flow. This analysis helps identify the critical point that causes soil erosion or settlement at a specific flow rate, providing a basis for soil protection and structural design.

[0044] Step S23: using the three-dimensional model of the reservoir dam to estimate the change of reservoir water body fluidity, and obtain reservoir water body fluidity change data; In the embodiment of the present invention, the three-dimensional model of the reservoir dam is integrated with the water flow simulation tool. Dynamic flow analysis is performed by inputting current water level data, rainfall, and inflow and outflow. The model simulates the flow rate, flow direction, and flow pattern of the water body under different operating conditions. This process uses computational fluid dynamics (CFD) methods to simulate the flow in detail to identify potential changes in water flow patterns and ensure that the dam design can cope with future flow changes.

[0045] Step S24: analyzing soil settlement around the reservoir based on the reservoir water body fluidity change data and the surrounding soil water flow critical velocity data to obtain soil settlement data around the reservoir.

[0046] In an embodiment of the present invention, the water body fluidity change data is input into the soil settlement analysis model. Combined with the soil water critical velocity data, the geomechanical model is used to evaluate the settlement of the soil under different flow conditions. By simulating the impact of water flow on the soil, the settlement area and its extent are analyzed. This analysis uses foundation settlement prediction methods, such as finite element analysis (FEA) or analytical methods, to accurately predict soil settlement, thereby ensuring the stability of the reservoir and its infrastructure.

[0047] Preferably, step S24 comprises the following steps: Step S241: Calculate the change of water flow rate according to the change data of water body fluidity of the reservoir to obtain the change data of water flow rate of the reservoir; Step S242: Calculating the water flow impact pressure on the soil around the reservoir according to the reservoir water flow velocity change data to obtain water flow impact pressure data; Step S243: simulating the surrounding soil water flow erosion based on the water flow impact pressure data and the reservoir water flow velocity change data on the surrounding soil water flow critical velocity data to obtain the soil water flow erosion data around the reservoir; Step S244: analyzing soil particles transported by water flow according to the soil water erosion data around the reservoir to obtain soil particle data transported by water flow in the reservoir; Step S245: Perform soil settlement analysis around the reservoir based on the soil particle data transported by reservoir water flow and the soil water erosion data around the reservoir to obtain soil settlement data around the reservoir.

[0048] In an embodiment of the present invention, the water flowability data of the reservoir under different water levels and flow conditions are input into the flow velocity calculation model. The change of water flow velocity in different time periods is calculated using fluid mechanics formulas in combination with the actual velocity and direction of the water flow. The water flow velocity change data is input into the impact pressure calculation model. According to the velocity, flow and direction of the water flow, the impact pressure of the water flow on the soil is calculated using fluid dynamics equations (such as the Bernoulli equation or the Navier-Stokes equation). The specific process includes combining the water flow velocity data with the physical properties of the soil (such as density and strength) to calculate the impact force of the water flow under different flow velocity conditions. Using the water flow impact pressure and flow velocity change data, a simulation analysis is performed through a soil erosion model. The specific operation includes inputting the water flow impact pressure, flow velocity change and soil type parameters, and using the soil erosion calculation formula (such as the Manning formula or the RUSLE formula) to simulate erosion. The erosion data is input into the particle transport analysis model. The model calculates the transport of soil particles by water flow based on the principles of fluid dynamics and particle physics. Use particle transport formulas, such as the Eulerian-Lagrangian model, to analyze the movement distance and distribution of soil particles under different water flow conditions. The water flow transport soil particle data obtained describes the migration characteristics of soil particles under the action of water flow. According to the reservoir water flow transport soil particle data and the soil water flow erosion data around the reservoir, the soil settlement analysis around the reservoir is carried out. The soil particle transport data and erosion data are input into the settlement analysis model. Use foundation settlement prediction methods, such as the finite element method or settlement calculation formulas, to evaluate the settlement of soil under the action of water flow. The analysis process includes calculating the soil settlement rate and settlement area, and evaluating the impact of water flow on soil settlement through soil settlement models (such as compressibility models).

[0049] Preferably, step S3 comprises the following steps: Step S31: Calculate the water level rise of the reservoir dam three-dimensional model according to the reservoir water body fluidity change data to obtain the reservoir water body water level rise data; Step S32: Calculating the dam water pressure distribution on the reservoir dam three-dimensional model according to the reservoir water level rise data to obtain the dam water pressure distribution data; Step S33: simulating heterogeneous settlement of the dam foundation on the three-dimensional model of the reservoir dam according to the soil settlement data around the reservoir to obtain heterogeneous settlement data of the dam foundation; Step S34: analyzing the internal stress distribution of the dam according to the heterogeneous settlement data of the dam foundation and the water pressure distribution data of the dam to obtain the internal stress distribution data of the dam; Step S35: performing a dam crack risk assessment based on the dam internal stress distribution data to obtain dam crack risk assessment data; Step S36: Calculate the water tightness of the dam according to the dam crack risk assessment data and the reservoir water body fluidity change data to obtain the reservoir dam water tightness data; Step S37: Calculate the reservoir capacity attenuation on the three-dimensional model of the reservoir dam according to the reservoir dam water tightness data and the dam crack risk assessment data to obtain the reservoir capacity attenuation data.

[0050] In the embodiment of the present invention, the data of the change of the fluidity of the water body in the reservoir is input into the three-dimensional modeling software to simulate the change of the water level. By using the principle of water body mechanics and the fluid dynamics model, the water level rise of the water body is calculated by analyzing the real-time data of the water velocity, flow rate and the change of the water body fluidity. The water level rise data is calculated by the model and reflects the actual water level change of the water body under different operating conditions. The water level rise data of the water body is imported into the three-dimensional model of the dam and analyzed by the pressure distribution calculation tool. According to the depth change of the water body and the water level rise data, the pressure distribution of each part of the dam is obtained by calculating the pressure gradient and the force of the water body on the dam. The settlement data is imported into the foundation settlement model, and the finite element analysis method is used to simulate the heterogeneous settlement of the dam foundation. The specific steps include setting the settlement parameters, considering the physical properties of different soil layers, such as compressibility and settlement rate, and simulating the deformation of the foundation under load. Combined with the foundation settlement and water body pressure data, the structural mechanics model is used to perform stress analysis. These data are input into the stress analysis tool to calculate the stress distribution of each part inside the dam. During the analysis, the elastic modulus and structural characteristics of the dam material need to be considered. The stress distribution diagram shows the stress concentration areas and uneven stress distribution faced by the dam structure under different load conditions. The crack risk assessment model is used to analyze the stress distribution data and identify the areas where cracks appear in the dam structure. The critical stress value for crack formation is calculated through stress analysis data, and compared with the actual stress distribution to assess the crack risk in each area. The watertightness calculation model is used to assess the watertightness of the dam by combining the crack risk assessment data and water flow information. The model input includes the location information, size and impact of water flow on the dam. The impact of cracks on the overall watertightness of the dam is assessed by simulating water flow penetration. The watertightness data and crack risk data are input into the capacity decay calculation model to simulate the attenuation of reservoir capacity under different conditions. The reservoir capacity calculation formula is used to assess the change in actual available capacity in combination with the impact of dam cracks on water storage capacity.

[0051] Preferably, step S6 comprises the following steps: Step S361: performing a reservoir dam rupture simulation on the reservoir dam three-dimensional model according to the dam crack risk assessment data to obtain reservoir dam rupture data; Step S362: Obtaining reservoir dam rupture complexity data and reservoir rupture length data according to the rupture complexity analysis and rupture length measurement of the reservoir dam rupture data; Step S363: performing dam seepage path analysis according to the reservoir dam rupture complexity data and the reservoir rupture length data to obtain reservoir dam rupture seepage path data; Step S364: estimating the reservoir dam seepage flow rate according to the reservoir dam rupture seepage flow path data and the reservoir water body fluidity change data to obtain the reservoir dam water seepage flow rate data; Step S365: Calculate the water tightness of the dam based on the water seepage volume data of the reservoir dam and the seepage path data of the reservoir dam rupture to obtain the water tightness data of the reservoir dam.

[0052] In an embodiment of the present invention, the crack risk assessment data is input into a three-dimensional modeling tool, and a numerical simulation method is used to simulate the rupture of the dam. During the simulation process, the position, size and extension direction of the crack are set, and the rupture mechanics model is used to simulate the impact of crack expansion on the dam structure. By gradually increasing the pressure and load of the crack, the rupture process of the dam is observed, the rupture situation of each step is recorded, and the reservoir dam rupture data is generated. The data obtained from the rupture simulation is analyzed in detail, and the length and complexity of the rupture are measured using an image processing tool. The rupture complexity analysis includes calculating the number of bifurcation points of the rupture and the irregularity of the crack boundary. These data are integrated into rupture complexity data and rupture length data to evaluate the specific impact of the rupture on the stability of the dam structure and determine the degree of rupture. Using the seepage analysis model, the rupture complexity data and rupture length data are input, and the water flow path in the rupture area is simulated by performing a detailed seepage path calculation on the dam structure. The specific steps include setting the boundary conditions in the seepage model, calculating the flow of water in the rupture area, and drawing a seepage path diagram to show how the water flow diffuses through the rupture area. Using the seepage calculation model, the seepage path data is combined with the water body fluidity data. The seepage of the dam is estimated by calculating the water flow on the seepage path. The specific operations include setting the fluid dynamics parameters in the seepage model, applying the corresponding fluidity equation, calculating the seepage of the dam under different water flow conditions, and inputting the seepage data and the seepage path data into the water tightness analysis model to evaluate the water tightness of the dam. The model includes parameters such as permeability coefficient and fracture seepage characteristics. By calculating the water tightness of the dam, the influence of fractures and seepage on the overall water tightness of the dam is evaluated. Finally, the water tightness data of the reservoir dam is obtained.

[0053] Preferably, step S4 comprises the following steps: Step S41: analyzing the reservoir dam inflow flow rate according to the reservoir capacity attenuation data to obtain the reservoir dam inflow flow rate data; Step S42: Calculate the efficiency attenuation of the dam generator set according to the water inflow data of the reservoir dam to obtain the efficiency attenuation data of the dam generator set; Step S43: conducting a dam design feasibility assessment on the reservoir dam design data according to the dam generator set efficiency attenuation data, the reservoir capacity attenuation data, and the soil settlement data around the reservoir, to obtain the reservoir dam design feasibility data; Step S44: optimizing the reservoir dam design on the reservoir dam three-dimensional model according to the reservoir dam construction feasibility data and the dam generator efficiency attenuation data to obtain reservoir dam design optimization data.

[0054] As an example of the present invention, refer to Figure 3 As shown, in this example, step S4 includes: Step S41: analyzing the reservoir dam inflow flow rate according to the reservoir capacity attenuation data to obtain the reservoir dam inflow flow rate data; In the embodiment of the present invention, the reservoir capacity decay data is input into the flow analysis tool, and the tool uses the principle of fluid dynamics to calculate the dam inflow flow. The specific method includes setting the historical water storage data and capacity change trend of the reservoir, applying the flow formula for calculation, and obtaining the current reservoir dam inflow flow data.

[0055] Step S42: Calculate the efficiency attenuation of the dam generator set according to the water inflow data of the reservoir dam to obtain the efficiency attenuation data of the dam generator set; In the embodiment of the present invention, a generator set performance model is used, and the water inlet flow data is input into the model to calculate the effect of the water flow on the efficiency of the generator set. The model includes the flow-efficiency relationship curve of the generator set and the effect of the water flow on the mechanical load of the generator set. During the calculation process, by gradually adjusting the water inlet flow value, the efficiency change of the generator set under different flow conditions is obtained, and the efficiency attenuation data of the dam generator set is generated.

[0056] Step S43: conducting a dam design feasibility assessment on the reservoir dam design data according to the dam generator set efficiency attenuation data, the reservoir capacity attenuation data, and the soil settlement data around the reservoir, to obtain the reservoir dam design feasibility data; In the embodiment of the present invention, the above data are integrated into a design evaluation model, which takes into account the impact of power generation efficiency, capacity decay and soil settlement on the dam structure and its operation. By analyzing the design parameters under different circumstances, it is evaluated whether the current design meets the actual needs. The principles of structural mechanics and soil mechanics are used in the evaluation process to determine the feasibility of the design, and finally generate the feasibility data of the dam design to indicate whether the design needs to be adjusted.

[0057] Step S44: optimizing the reservoir dam design on the reservoir dam three-dimensional model according to the reservoir dam construction feasibility data and the dam generator efficiency attenuation data to obtain reservoir dam design optimization data.

[0058] In the embodiment of the present invention, the feasibility data of the dam design and the efficiency attenuation data are input into the three-dimensional modeling and optimization tool. The tool optimizes the structure and function of the dam by adjusting the design parameters (such as the height and thickness of the dam body) to improve the operating efficiency and safety of the dam. The optimization process includes comprehensive consideration of the structural strength and stability, and finally obtains the optimized design data of the reservoir dam.

[0059] Preferably, the present invention also provides a water conservancy project life cycle management system based on digital twins, which is used to execute the water conservancy project life cycle management method. The water conservancy project life cycle management system includes: The reservoir dam three-dimensional model construction module obtains the data around the reservoir; designs the reservoir dam according to the data around the reservoir to obtain the reservoir dam design data; constructs the reservoir dam three-dimensional model according to the reservoir dam design data to obtain the reservoir dam three-dimensional model; The soil settlement analysis module around the reservoir collects the soil condition of the reservoir based on the data around the reservoir to obtain the soil condition data around the reservoir; uses the three-dimensional model of the reservoir dam to estimate the change of the fluidity of the reservoir water body and obtain the data of the change of the fluidity of the reservoir water body; analyzes the soil settlement around the reservoir based on the data of the change of the fluidity of the reservoir water body and the three-dimensional model of the reservoir dam to obtain the soil settlement data around the reservoir; The reservoir capacity attenuation calculation module calculates the dam water pressure distribution of the three-dimensional model of the reservoir dam according to the reservoir water body fluidity change data, and obtains the dam water body pressure distribution data; simulates the dam foundation heterogeneous settlement of the three-dimensional model of the reservoir dam according to the soil settlement data around the reservoir, and obtains the dam foundation heterogeneous settlement data; calculates the reservoir capacity attenuation of the three-dimensional model of the reservoir dam according to the dam foundation heterogeneous settlement data and the dam water body pressure distribution data, and obtains the reservoir capacity attenuation data; The reservoir dam design optimization module calculates the efficiency attenuation of the dam generator set according to the reservoir capacity attenuation data to obtain the efficiency attenuation data of the dam generator set; it optimizes the reservoir dam design of the three-dimensional model of the reservoir dam according to the efficiency attenuation data of the dam generator set to obtain the reservoir dam design optimization data.

[0060] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0061] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A water conservancy project full life cycle management method based on digital twins, characterized in that: The following steps are involved: Step S1: Obtaining data around the reservoir; Design the reservoir dam according to the data around the reservoir to obtain the design data of the reservoir dam; construct the three-dimensional model of the reservoir dam according to the design data of the reservoir dam to obtain the three-dimensional model of the reservoir dam; Step S2: collecting reservoir soil conditions according to reservoir surrounding data to obtain reservoir surrounding soil condition data; using the reservoir dam three-dimensional model to estimate the change of reservoir water body fluidity to obtain reservoir water body fluidity change data; performing reservoir surrounding soil settlement analysis on the reservoir dam three-dimensional model according to the reservoir water body fluidity change data and the reservoir surrounding soil condition data to obtain the reservoir surrounding soil settlement data; Step S3: Calculate the water pressure distribution of the reservoir dam three-dimensional model according to the reservoir water body fluidity change data to obtain the dam water body pressure distribution data; simulate the heterogeneous settlement of the dam foundation of the reservoir dam three-dimensional model according to the soil settlement data around the reservoir to obtain the heterogeneous settlement data of the dam foundation; calculate the reservoir capacity attenuation of the reservoir dam three-dimensional model according to the heterogeneous settlement data of the dam foundation and the dam water body pressure distribution data to obtain the reservoir capacity attenuation data; Step S4: Calculate the efficiency attenuation of the dam generator set according to the reservoir capacity attenuation data to obtain the efficiency attenuation data of the dam generator set; The reservoir dam design is optimized based on the dam generator efficiency attenuation data and the reservoir capacity attenuation data to obtain the reservoir dam design optimization data.

2. The water conservancy project full life cycle management method based on digital twin according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: Acquire data around the reservoir; Step S12: Analyze the water resource demand of the data around the reservoir based on the digital twin to obtain the water resource demand data around the reservoir; Step S13: Designing the reservoir dam according to the reservoir water resource demand data and the reservoir surrounding data to obtain the reservoir dam design data; Step S14: constructing a three-dimensional model of the reservoir dam according to the reservoir dam design data to obtain a three-dimensional model of the reservoir dam.

3. The method for managing the entire life cycle of a water conservancy project based on digital twins according to claim 2 is characterized in that: Step S13 includes the following steps: Step S131: Obtain historical rainfall data around the reservoir; Step S132: extracting the terrain around the reservoir based on the data around the reservoir to obtain the terrain data around the reservoir; Step S133: collecting surrounding geological conditions according to the terrain data around the reservoir to obtain geological condition data around the reservoir; Step S134: Calculate the water storage volume of the reservoir according to the water resource demand data around the reservoir to obtain the water storage volume data of the reservoir; Step S135: Count the historical maximum rainfall according to the historical rainfall data around the reservoir to obtain the historical maximum rainfall data around the reservoir; Step S136: predicting the highest point that the water level can reach based on the reservoir water storage volume data, the historical maximum rainfall data around the reservoir, and the terrain data around the reservoir to obtain the predicted data of the highest point that the water level can reach; Step S137: Design the reservoir dam according to the prediction data of the highest point that the water level can reach, the terrain data around the reservoir, and the geological condition data around the reservoir to obtain the reservoir dam design data.

4. The method for managing the entire life cycle of a water conservancy project based on digital twins according to claim 3 is characterized in that: The design of the reservoir dam based on the predicted data of the highest water level, the terrain data around the reservoir, and the geological data around the reservoir includes the following steps: Calculate the height of the reservoir dam based on the predicted data of the highest point that the water level can reach and the terrain data around the reservoir to obtain the height data of the reservoir dam; The water depth pressure at the lowest water level of the reservoir is calculated based on the reservoir dam height data and the predicted data of the highest water level point, and the water depth pressure data at the lowest water level of the reservoir is obtained; According to the water depth pressure data at the lowest water level of the reservoir, the geological condition data around the reservoir are used to extract the stable geological water pressure bearing area, and the geological water pressure bearing stable area data is obtained; The site selection data for reservoir dam construction is obtained by using the regional data of geological water pressure bearing stability and the terrain data around the reservoir to perform site intersection operations; Conduct reservoir water velocity test based on reservoir dam construction site selection data to obtain reservoir dam construction site selection water velocity data; The dam thickness data is calculated based on the water depth pressure data at the lowest water level of the reservoir and the water flow velocity data of the reservoir dam construction site selection to obtain the reservoir dam thickness data; The reservoir dam is designed using the reservoir dam height data, reservoir dam thickness data and reservoir dam construction site selection data to obtain the reservoir dam design data.

5. The method for managing the entire life cycle of a water conservancy project based on digital twins according to claim 1 is characterized in that: Step S2 includes the following steps: Step S21: collecting soil condition data of the reservoir according to the data of the reservoir surrounding area to obtain soil condition data of the reservoir surrounding area; Step S22: analyzing the critical flow velocity of soil water flow on the soil condition data around the reservoir based on the digital twin to obtain the critical flow velocity data of the surrounding soil water flow; Step S23: using the three-dimensional model of the reservoir dam to estimate the change of reservoir water body fluidity, and obtain reservoir water body fluidity change data; Step S24: analyzing soil settlement around the reservoir based on the reservoir water body fluidity change data and the surrounding soil water flow critical velocity data to obtain soil settlement data around the reservoir.

6. The method for managing the entire life cycle of a water conservancy project based on digital twins according to claim 5 is characterized in that: Step S24 includes the following steps: Step S241: Calculate the change of water flow rate according to the change data of water body fluidity of the reservoir to obtain the change data of water flow rate of the reservoir; Step S242: Calculating the water flow impact pressure on the soil around the reservoir according to the reservoir water flow velocity change data to obtain water flow impact pressure data; Step S243: simulating the surrounding soil water flow erosion based on the water flow impact pressure data and the reservoir water flow velocity change data on the surrounding soil water flow critical velocity data to obtain the soil water flow erosion data around the reservoir; Step S244: analyzing soil particles transported by water flow according to the soil water erosion data around the reservoir to obtain soil particle data transported by water flow in the reservoir; Step S245: Perform soil settlement analysis around the reservoir based on the soil particle data transported by reservoir water flow and the soil water erosion data around the reservoir to obtain soil settlement data around the reservoir.

7. The method for managing the entire life cycle of a water conservancy project based on digital twins according to claim 1 is characterized in that: Step S3 includes the following steps: Step S31: Calculate the water level rise of the reservoir dam three-dimensional model according to the reservoir water body fluidity change data to obtain the reservoir water body water level rise data; Step S32: Calculating the dam water pressure distribution on the reservoir dam three-dimensional model according to the reservoir water level rise data to obtain the dam water pressure distribution data; Step S33: simulating heterogeneous settlement of the dam foundation on the three-dimensional model of the reservoir dam according to the soil settlement data around the reservoir to obtain heterogeneous settlement data of the dam foundation; Step S34: analyzing the internal stress distribution of the dam according to the heterogeneous settlement data of the dam foundation and the water pressure distribution data of the dam to obtain the internal stress distribution data of the dam; Step S35: performing a dam crack risk assessment based on the dam internal stress distribution data to obtain dam crack risk assessment data; Step S36: Calculate the water tightness of the dam according to the dam crack risk assessment data and the reservoir water body fluidity change data to obtain the reservoir dam water tightness data; Step S37: Calculate the reservoir capacity attenuation on the three-dimensional model of the reservoir dam according to the reservoir dam water tightness data and the dam crack risk assessment data to obtain the reservoir capacity attenuation data.

8. The method for managing the entire life cycle of a water conservancy project based on digital twins according to claim 7 is characterized in that: Step S36 includes the following steps: Step S361: performing a reservoir dam rupture simulation on the reservoir dam three-dimensional model according to the dam crack risk assessment data to obtain reservoir dam rupture data; Step S362: Obtaining reservoir dam rupture complexity data and reservoir rupture length data according to the rupture complexity analysis and rupture length measurement of the reservoir dam rupture data; Step S363: performing dam seepage path analysis according to the reservoir dam rupture complexity data and the reservoir rupture length data to obtain reservoir dam rupture seepage path data; Step S364: estimating the reservoir dam seepage flow rate according to the reservoir dam rupture seepage flow path data and the reservoir water body fluidity change data to obtain the reservoir dam water seepage flow rate data; Step S365: Calculate the water tightness of the dam based on the water seepage volume data of the reservoir dam and the seepage path data of the reservoir dam rupture to obtain the water tightness data of the reservoir dam.

9. The method for managing the entire life cycle of a water conservancy project based on digital twins according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: analyzing the reservoir dam inflow flow rate according to the reservoir capacity attenuation data to obtain the reservoir dam inflow flow rate data; Step S42: Calculate the efficiency attenuation of the dam generator set according to the water inflow data of the reservoir dam to obtain the efficiency attenuation data of the dam generator set; Step S43: conducting a dam design feasibility assessment on the reservoir dam design data according to the dam generator set efficiency attenuation data, the reservoir capacity attenuation data, and the soil settlement data around the reservoir, to obtain the reservoir dam design feasibility data; Step S44: optimizing the reservoir dam design on the reservoir dam three-dimensional model according to the reservoir dam construction feasibility data and the dam generator efficiency attenuation data to obtain reservoir dam design optimization data.

10. A water conservancy project full life cycle management system based on digital twins, characterized in that: Used to execute the water conservancy project full life cycle management method as claimed in claim 1, the water conservancy project full life cycle management system comprises: The reservoir dam three-dimensional model construction module obtains the data around the reservoir; designs the reservoir dam according to the data around the reservoir to obtain the reservoir dam design data; constructs the reservoir dam three-dimensional model according to the reservoir dam design data to obtain the reservoir dam three-dimensional model; The soil settlement analysis module around the reservoir collects the soil condition of the reservoir based on the data around the reservoir to obtain the soil condition data around the reservoir; uses the three-dimensional model of the reservoir dam to estimate the change of the fluidity of the reservoir water body and obtain the data of the change of the fluidity of the reservoir water body; analyzes the soil settlement around the reservoir based on the data of the change of the fluidity of the reservoir water body and the three-dimensional model of the reservoir dam to obtain the soil settlement data around the reservoir; The reservoir capacity attenuation calculation module calculates the dam water pressure distribution of the three-dimensional model of the reservoir dam according to the reservoir water body fluidity change data, and obtains the dam water body pressure distribution data; simulates the dam foundation heterogeneous settlement of the three-dimensional model of the reservoir dam according to the soil settlement data around the reservoir, and obtains the dam foundation heterogeneous settlement data; calculates the reservoir capacity attenuation of the three-dimensional model of the reservoir dam according to the dam foundation heterogeneous settlement data and the dam water body pressure distribution data, and obtains the reservoir capacity attenuation data; The reservoir dam design optimization module calculates the efficiency attenuation of the dam generator set according to the reservoir capacity attenuation data to obtain the efficiency attenuation data of the dam generator set; it optimizes the reservoir dam design of the three-dimensional model of the reservoir dam according to the efficiency attenuation data of the dam generator set to obtain the reservoir dam design optimization data.

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