110 results about "Dam break" patented technology

The invention provides a flood peak evolution path and dam break risk early warning method and system. According to the method, a time-space coupling water conservancy data set is constructed by fusing multi-dimensional water conservancy monitoring data and regional rainfall prediction information, and a basin topology perception model is established. And further performing mode matching on the parameters and a historical dam break event characteristic spectrum, and generating a dynamic response strategy set including a flood storage and detention area capacity allocation scheme by correcting a space weight of a matching result. And finally, based on a watershed topology perception model, matching the strategy set with historical dam break features, realizing accurate identification of a flood peak evolution path and graded early warning of dam break risks, outputting a water conservancy analysis report containing risk grades, and realizing closed-loop management from data fusion and dynamic prediction to risk decision. According to the technical scheme provided by the invention, the efficiency and accuracy of intelligent analysis of the water conservancy data can be improved.

The invention provides a multi-mode tailing pond dam break digital twinning emergency deduction and decision optimization method, which comprises the following steps of: firstly, constructing a high-precision three-dimensional scene model, performing simulation calculation on the high-precision three-dimensional tailing pond model based on a finite element model to obtain a dam body stress-strain field, and performing simulation calculation on the dam body stress-strain field based on ANSYS + reinforcement learning. And predicting a dam break probability distribution diagram by using the dam body stress-strain field and the current environment state, generating a rescue scheduling scheme based on the dam break probability distribution diagram and the resource distribution data, building a dynamic virtual deduction scene for exercise, and verifying and optimizing the rescue scheduling scheme according to exercise record data. And a final rescue scheduling scheme is obtained. According to the method, the ANSYS + reinforcement learning hybrid engine is utilized to reinforce the deduction precision, dam break path prediction, optimal resource scheduling and plan self-optimization closed loop are realized, the problems of data fusion distortion, deduction stiffness, decision lag and the like in the traditional technology are solved, and the method is particularly suitable for variable working conditions such as tailing pond seepage field sudden change and extreme weather.

The invention discloses a buttress dam break pre-evaluation method and device based on a knowledge graph, and a medium, and relates to the technical field of dam break pre-estimation. The method comprises the steps of obtaining multi-source data of buttress dam monitoring points, wherein the monitoring points are located at a dam body and a joint of the buttress dam; fusing the multi-source data, extracting entities and entity relationships of the multi-source data through natural language processing, and constructing a knowledge graph; performing mode layer updating and data layer updating on the knowledge graph based on preset time; selecting a basic event and an intermediate event according to an entity relationship and entities in the knowledge graph; performing sequence modeling on the basic events by using the improved recurrent neural network, and identifying dam break types; and performing fault tree evaluation on the dam break type to obtain a risk index of the dam break type. By means of the method, comprehensive consideration of the logic relation among complex environmental factors, faults and reasons is achieved.

The invention discloses a water conservancy facility full-period informatization management method and system based on digital twinning, and relates to the technical field of water conservancy informatization management, and the method comprises the steps: collecting water conservancy facility data, constructing a water conservancy facility digital twinning model, constructing an interactive structure body through employing three-dimensional geometric modeling, topological coding, material attribute and operation state fields, and constructing a water conservancy facility digital twinning model. Node mapping, attribute inheritance and time evolution rules are established; on-site progress, quality and deviation data are collected through a construction period sensing device, a state-driven mapping mechanism is designed, various data are dynamically mapped to a digital twin model of the water conservancy facility, and a structure-environment collaborative sensing mechanism is constructed in an operation stage; based on the digital twinborn model data of the water conservancy facility, a risk identification model is established, and the dam break risk, gate clamping stagnation, pump station failure and channel clogging are predicted. According to the method, linkage of water conservancy facility multi-source sensing, digital twin mapping and risk identification is realized, and the operation safety monitoring precision and the regulation and control efficiency are improved.

The invention belongs to the technical field of hydraulic engineering, and particularly discloses an embankment burst and flood routing simulation method which comprises the following steps: step 1, subdividing a breach area of an embankment by adopting a rectangular grid, and respectively subdividing a river channel on one side of the embankment and a protection area on the other side of the embankment by adopting an unstructured grid; step 2, flood information in the unstructured grid is acquired, and the flood information is interpolated into the rectangular grid; and step 3, determining outburst information of the breach area by using the water-soil coupling kinetic model, interpolating the outburst information into the unstructured grid, and repeating the step 2 and the step 3 until a preset condition is met. According to the method, a water-soil coupling dynamic model is adopted to describe the dike burst process, parameters such as the burst rate and the final breach size of an existing model do not need to be manually given, and full-automatic simulation of the dike burst process is achieved. According to the method, the structure-non-structure double grid technology is adopted, and the precision and efficiency of the embankment outburst process and outburst flood routing calculation are both considered.

The invention discloses a dynamic topology mapping and GPU heterogeneous flood coupling model real-time early warning method, and solves the problems of inflexible coupling of a one-dimensional model and a two-dimensional model, low calculation efficiency, poor dynamic response capability and the like in traditional flood simulation. A dynamic topology mapping mechanism is introduced to respond to emergencies such as dike burst and overflow in real time, the calculation efficiency is remarkably improved by utilizing a GPU heterogeneous parallel architecture, rapid and accurate simulation of the whole process of flood formation, evolution and submerging is achieved, reliable technical support is provided for flood control dispatching and emergency decision making, and the method is suitable for large-scale popularization and application. The method comprises the following steps: constructing a two-dimensional hydrodynamic model based on an unstructured grid, establishing a dynamic topology mapping mechanism and realizing GPU parallel numerical calculation; a two-dimensional model lateral connection coupling mechanism is constructed, dam overtopping flow is calculated in real time, and breach flow dynamic calculation of an improved DAMBRK method is carried out; multi-target parameter calibration, multi-dimensional model verification and one-two-dimensional model GPU collaborative parallel computing are realized.

The invention provides a tailing pond dam break whole process simulation method and system, and the method comprises the steps: building a three-dimensional geological grid model according to the earth surface point cloud data of a target region in cooperation with drilling data, and solving an initial ground stress field through a virtual mass method and setting a stress unbalance rate condition; in the landslide simulation stage, mountain fracture process simulation is carried out based on an initial ground stress field and landslide impact force, and a fracture area boundary and pore water pressure distribution are obtained; when the displacement of the dam body in the disaster response suddenly changes or the stress exceeds a threshold value, a dam break simulation stage of the deformation failure area is started; in a dam break simulation stage, simulating a sand flow movement path based on the boundary of the destroyed area and topographic data; and finally, generating a disaster-forming path map, a stacking thickness cloud map and an influence range thermodynamic cloud map based on the mud and sand flow movement path. Limitations of a traditional method are broken through, full-process high-precision efficient simulation of deformation, damage, burst and disaster formation of tailing pond dam break is achieved for the first time, and quantitative prevention and control bases are provided for high-risk scenes.

The invention discloses a reservoir dam risk assessment method, which comprises the following steps of: constructing an index system taking human, technology, organization and environment as criterion layers, performing weighting on indexes by adopting AHP and improved CRITIC methods, performing weighting combination based on a game theory method to obtain a combination weight of each index, and realizing dynamic weighting of top layer indexes by using an incentive variable weight method. Compared with the prior art, the reservoir dam risk assessment method has the advantages that human factor analysis and engineering dam break are combined; index weight combination weighting is carried out; using a variable weight risk assessment method; and the accuracy and the practical property of reservoir dam risk assessment are realized.

The invention provides a tailing pond seepage sensitivity analysis and dam break early warning method based on fracture characteristics, and the method comprises the steps: obtaining a collection image of a tailing pond dam body based on a computer vision technology, carrying out the analysis processing of the collection image, determining a joint fracture region and joint fracture characteristics, and achieving the accurate obtaining of the joint fracture characteristics of the tailing pond. And providing an accurate data basis for the seepage sensitivity of the tailing pond, determining the infiltration surface distribution and the hydraulic gradient distribution of the tailing pond dam body based on the joint fissure area and the joint fissure characteristics, carrying out seepage sensitivity analysis calculation on the tailing pond dam body to obtain a seepage calculation result, and calculating the seepage sensitivity of the tailing pond dam body based on a standard result. Dam break judgment is carried out on various types of seepage calculation results, early warning reminding is carried out according to the dam break judgment, accurate analysis and early warning of the stability of the tailings pond are achieved, and the safety of the tailings pond is ensured.

The invention provides a tailing dam instability situation multi-source information fusion early warning method. The method comprises the steps that tailing dam parameters of a tailing dam are collected, and first multi-source early warning parameters are determined from the tailing dam parameters; obtaining a landform model of the tailing dam, and establishing a multi-scale multi-factor coupling mechanical model of the tailing dam based on the landform model and the first multi-source early warning parameter; inputting the parameters of the tailing dam into a multi-scale multi-factor coupling mechanical model to predict and simulate the dam break process of the tailing dam to obtain a prediction and simulation result; and on the basis of the prediction simulation result, early warning is carried out on instability of the tailing dam. Therefore, according to the scheme, the multi-scale multi-factor coupling mechanical model is used for early warning, physical mechanisms and interaction of the tailing dam on different scales are considered, the instability trend of the tailing dam can be predicted more accurately by performing coupling analysis on multiple factors, and the early warning precision is improved.

The invention provides a DEM-based method for extracting dam break flood inundation range and water depth of small and medium-sized reservoirs in hilly areas, and belongs to the technical field of dam break flood inundation analysis. The method comprises the following steps: firstly, calculating dam break flow at a reservoir dam site; secondly, extracting a cross section of a downstream river channel of the small and medium-sized reservoir, and deducing dam break flood peak flow and peak flow evolved to each control section along the downstream river channel; then, the highest water level of each river channel cross section is calculated according to the peak flow of the section, and the flood inundation range is obtained through the inundation water level; and finally, on the basis of the grid type DEM topographic data, the submerging water depth of each topographic grid unit in the submerging range is calculated in batches, so that reservoir downstream region dam break flood submerging and water depth calculation analysis is realized. The problem that a traditional simple submerging model cannot calculate submerging water depth can be solved, meanwhile, submerging range and water depth calculation is carried out based on DEM topographic data, and compared with a traditional hydrodynamic model, calculation is simpler and more convenient, and a model result is more stable.

The invention discloses a cascade reservoir continuous dam break two-dimensional flood simulation method and device and a medium, and relates to the technical field of hydrodynamic modeling and flood disaster simulation. The method comprises the steps that under the condition that the regulation and storage effect of an interval reservoir and the influence of continuous dam break are not considered, on the basis of data related to a cascade reservoir, a flood disaster simulation model is established; carrying out overall two-dimensional modeling on the cascade reservoir to obtain an overall two-dimensional hydrodynamic model and a maximum submerging range; step-by-step segmentation is carried out on the cascade reservoirs according to the number of the reservoirs, two-dimensional modeling is carried out on the reservoirs in each segment, and segment two-dimensional models are obtained; in the step-by-step simulation process, based on the dam break rule of the reservoir in each step, an overall two-dimensional hydrodynamic model or a segmented two-dimensional model is adopted for simulation, and a submerging result of the segmented two-dimensional model of each step is obtained; and superposing the maximum submerging range and the submerging result, and finally generating a cascade reservoir dam break flood risk map. According to the method, the calculation efficiency and accuracy of cascade reservoir continuous dam break simulation analysis can be improved.

The invention provides a quantitative risk assessment method and system for an ice rock collapse-river blockage-dam break flood disaster chain. The method comprises the following steps: acquiring an ice rock collapse risk grade index by adopting a BP neural network improved by an Adam optimizer; if the ice rock collapse occurs, correcting and calculating an ice rock collapse movement path based on a D8 algorithm in combination with a rock-soil friction coefficient, correcting the volume in real time through an erosion-accumulation dynamic balance model, and constructing a river blocking risk grade index in combination with the river entering volume and speed; the stability of the dam body is evaluated through a dynamic catchment area model and a Sigmoid function, and the dam break risk is calculated in combination with the ratio of the volume to the area; and if the dam break disaster does not occur in the barrier dam, integrating the ice rock collapse risk grade, the river blocking risk grade and the dam break risk grade index, and evaluating the comprehensive risk of the disaster chain. According to the method, disaster prediction of each stage is realized through neural network improvement, path optimization analysis and variance tracking change, and comprehensive risks are evaluated through multi-element coupling.

The invention discloses a glacier lake dam break emergency treatment method and equipment, a telescopic pipeline is erected on two sides of a dam body of a glacier lake, two ends of the telescopic pipeline are closed by valves, one end of the telescopic pipeline is submerged below the water surface of the glacier lake, and the other end of the telescopic pipeline extends to the outer side of the dam body and is lower than the water surface of the glacier lake. The telescopic pipeline is filled with lake water through another small-diameter rubber pipe with a submersible pump, so that air in the telescopic pipeline is completely discharged. And then valves at the two ends of the telescopic pipe are opened, and the lake water is discharged from the telescopic pipe through siphoning. Large-flow drainage can be achieved through the large-diameter telescopic pipeline, the lake water level is rapidly lowered, and the dam break risk is effectively relieved. The telescopic pipeline does not need to be filled with water in advance, is light in weight, is easy to hoist and install, and can be quickly filled and exhaust air. A small-diameter rubber pipe is used for filling, a high-power submersible pump is not needed, energy consumption is low, the overall weight of equipment is small, and rapid emergency arrangement is facilitated.

The invention discloses an earth and rockfill dam burst peak flow prediction method and a storage medium, and belongs to the technical field of hydraulic engineering technologies. On the basis of continuous arrangement and expansion of a historical database, a comprehensive database containing outburst case information of 295 earth and rockfill dams is formed, and correlation analysis is carried out on different dam break parameters and outburst peak discharge. Extracting five influence parameters of reservoir capacity above the bottom of the breach during dam break, dam height, dam reservoir capacity, final depth of the breach and water depth above the bottom of the breach during outburst, and constructing a new earth and rockfill dam outburst parameter prediction model considering different dam types and outburst modes. Compared with 20 groups of typical parameter models existing at home and abroad, the calculation result shows that the root mean square error (Erms) and the correlation coefficient (R2) of the provided prediction model are 0.38 and 0.82 respectively, and compared with other models, the model has certain advantages, and the accuracy of the model is verified.

The invention discloses a tailing pond multi-dimensional data fusion-based disaster hidden danger identification and early warning method, and relates to the related field of disaster hidden danger identification and early warning, and the method comprises the steps: carrying out the data fusion of a multi-dimensional data set, generating a multi-dimensional data fusion result, carrying out the quick deduction of a plurality of environment parameters and the multi-dimensional data fusion result, and carrying out the early warning of the disaster hidden danger. Constructing a tailings pond catastrophe influence assessment mathematical model to perform risk assessment on the tailings pond, generating a plurality of risk levels, analyzing tailings pond dam break trigger criteria, generating a plurality of trigger indexes of the tailings pond to perform sensitivity analysis, determining a disaster trigger sensitivity coefficient and the plurality of risk levels to perform disaster hidden danger identification, and determining the disaster trigger sensitivity coefficient. And generating a disaster early warning signal and combining with the multi-dimensional data set to carry out disaster warning, and formulating emergency response measures to carry out emergency response on the disaster hidden danger of the tailings pond. The technical problems of real-time analysis and comprehensive evaluation of tailings pond data are solved, and the technical effects of improving the recognition accuracy of hidden danger and effectively performing early warning response are achieved.

The invention relates to a test device and method for simulating cascade reservoir dam break flood wave impact, and belongs to the technical field of dam break tests, the test device comprises a test pool, and the upper surface of the test pool is recessed downwards to form a water tank; the length direction of a water tank is arranged in the X direction, a gate assembly and a dam model assembly are arranged in the water tank, and the gate assembly and the dam model assembly divide the water tank into a water storage area, a propagation area and a containing area in sequence; the propagation area is provided with a simulation board assembly; a support frame is erected at the upper end of the test pool, and a panoramic camera is mounted on the support frame; a plurality of water flow velocity sensors are mounted on the side surface of the propagation area; a plurality of pressure sensors are installed on the surface of the side, close to the gate assembly, of the dam model assembly, and the pressure sensors can monitor the impact force generated when water flow impacts the simulation plate assembly. And a control panel is mounted on the test pool. According to the device and the method, different types of dam break scenes can be simulated, and more accurate and reliable experimental data can be provided for actual conditions.

The invention provides a geological disaster identification method based on seismic wave dynamics and kinematics characteristics, the geological disaster is mountain torrent or debris flow, and the method comprises the following steps: collecting seismic signals in a geological disaster potential risk area; the seismic signals are preprocessed; extracting early warning parameters from the pre-processed seismic signal, wherein the early warning parameters comprise a long and short time window energy ratio, a time-frequency spectrum parameter, a power spectrum density and a seismic signal duration; establishing an earthquake prediction model of the single-measuring-point geological disaster according to the extracted early warning parameters; fusing the earthquake prediction models of the geological disasters at multiple measuring points, and judging whether the earthquake signals are earthquake signals triggered by the geological disasters or not; and when it is judged that the seismic signal is triggered by the geological disaster flow, real-time early warning information issuing is carried out on the downstream risk area. The method can be applied to monitoring and early warning of geological disasters caused by artificial or natural activities such as mountain torrents, dam break, landslides, collapse and the like, and has wide engineering technology application and scientific research prospects.

The invention relates to a dam burst scene unmanned aerial vehicle monitoring method and system based on artificial intelligence. The method comprises the steps that hydrological data, meteorological data, satellite image data and topographic map data are acquired and input into a monitoring area identification artificial intelligence model, and target monitoring area risk level information and target monitoring area detection range information are generated; distributing the number of unmanned aerial vehicles and a preset route of each unmanned aerial vehicle based on the target monitoring area risk level information and the target monitoring area detection range information; controlling each unmanned aerial vehicle to fly along a corresponding preset route, and acquiring target monitoring data of each unmanned aerial vehicle; and inputting the target monitoring data of each unmanned aerial vehicle into the dam bursting and breaking scene analysis artificial intelligence model to generate a dam bursting and breaking scene analysis result. By adopting the method, high efficiency, accuracy and real-time performance of dam burst monitoring can be realized through multi-source data driving, dynamic task allocation and artificial intelligence model optimization.

The invention provides a three-dimensional lithium battery mine visualization system based on digital twinning, and the system comprises a physical sensing layer which is disposed at a lithium battery mine site, and comprises a plurality of sensor networks used for collecting geologic bodies, production equipment, environment parameters, personnel positions, and vehicle states; and the data interaction layer comprises a data integration platform and an edge computing node, and is used for carrying out cleaning, fusion, protocol conversion and edge side preliminary analysis on the multi-source heterogeneous data uploaded by the physical sensing layer, and uploading the multi-source heterogeneous data to a cloud. By integrating the slope monitoring sensor and the professional analysis model, real-time evaluation and advanced early warning of the slope stability and the tailing pond safety are achieved, major accidents such as collapse and dam break are effectively prevented, meanwhile, the harmful element diffusion model is utilized, and the safety of the tailing pond is improved. Migration paths of fluoride dust, radioactive substances and potential leakage pollutants in the atmosphere and the water system are dynamically simulated, accurate decision support is provided for environmental risk emergency response, and the influence on surrounding ecology is reduced to the maximum extent.

The invention belongs to the technical field of machine learning, and discloses an earth and rockfill dam outburst peak flow prediction method based on an elite strategy, and the method comprises the steps: obtaining historical earth and rockfill dam outburst feature data and a corresponding outburst peak flow to construct an earth and rockfill dam outburst data set; constructing a BP neural network, and improving the genetic algorithm by adopting an elitist strategy in the selection, intersection and variation processes of the genetic algorithm to obtain an improved genetic algorithm; taking the weight and bias of the BP neural network as individuals of the improved genetic algorithm, and optimizing the BP neural network by using the improved genetic algorithm to obtain an improved GA-BP neural network based on an elitist strategy; inputting the data in the data set into a GA-BP neural network to obtain a predicted outburst peak flow; based on an elitist strategy improved GA-BP neural network model, the accuracy and real-time performance of dam break peak flow prediction are greatly improved, and timely and effective decision support is provided for disaster prevention and reduction and emergency response; and the common local optimal solution difficulty in the traditional GA is also avoided.

The application discloses a soil-rock dam reinforcing and enhancing structure for preventing over-standard overflow dam break and a construction method thereof. The structure comprises a soil-rock dam filling body, a vertical anti-seepage core wall arranged in the soil-rock dam filling body, and a composite high-strength fiber three-dimensional membrane arranged on the surface of the dam slope after regulation. The membrane body is unfolded along the slope surface and is reinforced by a pressing plate type fixing anchor bolt and a fiber membrane three-dimensional rivet. The row-to-row spacing of the fixing anchor bolt is 20-50 cm, so that the composite membrane is tightly attached to the dam body. The rigid structure and the flexible protection material are organically combined, the dam body's erosion resistance and durability are significantly improved while the flood discharge capacity is ensured, the construction method is simple, the cost is low, and the method is suitable for flood control reinforcement and safe operation of various soil-rock dams.

The invention discloses a dam break possibility prediction method. A target dam and an associated water area are divided into a plurality of evaluation areas based on a first preset rule; collecting earth surface displacement data and foundation permeability data for the dam part of each evaluation area, and synchronously collecting historical hydrological data and real-time hydrological data for the water area part of each evaluation area; fusing the earth surface displacement data and the foundation permeability data as physical elements of the assessment areas, fusing the historical hydrological data and the real-time hydrological data as hydrological elements of the assessment areas, performing multi-source coupling calculation on the physical elements and the hydrological elements, and outputting dynamic risk factors corresponding to the assessment areas; determining a globally unified target risk threshold value based on the structure limit parameters and the dam break case statistical characteristics; and searching the shortest risk conduction path meeting the critical slope constraint through a graph theory algorithm. According to the method, the risk conduction intensity of the adjacent areas is quantified by establishing the chain topology network, and the most easily-burst path is identified by combining the critical slope constraint.

The invention relates to the field of mine geologic modeling, in particular to a dynamic geologic modeling method and system based on self-adaptive updating of multi-source heterogeneous data. The method comprises the steps that a tailings pond state feature data set is acquired, and a time-space lag prediction model is constructed through a machine learning method according to the tailings pond state feature data set; a tailing pond operation plan information set is obtained, and based on the tailing pond operation plan information set and the current ore pulp liquid level state, a time-space lag prediction model is utilized to predict a pore water pressure change information set in the tailing dam in the future period; and dynamically evaluating the stability of the tailing dam according to the pore water pressure change information set, and outputting stability early warning information. In the mine geologic modeling process, timely configuration of emergency resources and accurate control of prevention and control opportunities are achieved, and linkage dam body instability and disastrous dam break accidents are further reduced.

The proposed method and system for dam-break flood emergency evacuation route planning based on an improved NSGA-III integrates dam-break flood simulation, evacuation point and refuge point selection, multi-objective optimization, and heuristic strategies. This method can achieve efficient evacuation route optimization for groups of people with different priorities under extreme dam-break scenarios, thereby improving overall evacuation efficiency and priority. By conducting two-dimensional unsteady flow dam-break simulation in HEC-RAS and combining the scientific selection and prioritization of evacuation points and refuge points using the ArcGIS Pro platform, an evacuation optimization model that adapts to the spatial distribution characteristics of flood risk is constructed.

The application relates to the field of mine geological modeling, in particular to a dynamic geological modeling method and system based on adaptive updating of multi-source heterogeneous data. The method comprises the following steps: acquiring tailing pond state feature data set, constructing a time-space lag prediction model through a machine learning method according to the tailing pond state feature data set; acquiring a tailing pond operation plan information set, predicting a pore water pressure change information set inside a tailing dam in a future period of time by using the time-space lag prediction model based on the tailing pond operation plan information set and a current ore pulp liquid level state; and performing dynamic evaluation of tailing dam stability according to the pore water pressure change information set and outputting stability early warning information. In the mine geological modeling process, timely allocation of emergency resources and accurate grasp of prevention and control time are realized, and chain instability of dam body and disastrous dam break accidents are reduced.

Embodiments of the present application disclose a reservoir over-standard flood inundation risk zoning method, device and equipment, by determining the reservoir siltation influence probability factor and the reservoir dam break influence probability factor under the siltation condition, the reservoir siltation influence probability factor and the reservoir dam break influence probability factor are used to calibrate the reservoir inundation comprehensive risk degree of siltation-dam break double influence probability under the over-standard flood condition, and the K-means clustering algorithm is used to cluster and analyze the reservoir inundation comprehensive risk degree of each grid calculation unit, and finally the flood risk grade is determined. The technical problem of low accuracy of prediction and zoning of flood inundation risk in the prior art for the reservoir area with high sediment concentration and weak dredging capacity is solved, and a scientific basis and certain technical support are provided for reservoir flood inundation risk assessment and disaster prevention and mitigation planning in high sediment concentration basin areas.

The invention discloses a rule and case dual-driven dam overtopping and dam break emergency evacuation decision knowledge recommendation method and system. The method comprises the following steps: constructing a heterogeneous domain knowledge graph including flood prevention regulations, emergency plan rules and historical dam overtopping and dam break disaster cases; acquiring real-time water and rain condition time sequence data and a disaster-affected area risk grid image generated by calculation of a hydrodynamic model, and generating a digital instance of a current disaster scene in combination with static engineering parameters input by a user; inputting the digital instance into a rule reasoning track and a case reasoning track at the same time for reasoning to obtain a double-track reasoning result; performing fusion judgment on double-track reasoning results, and outputting a forced evacuation instruction or generating a suggestion scheme based on a constructed game income matrix; generating a comprehensive decision report containing personnel transfer suggestions, regulation basis and similar case reference based on the result of fusion judgment; according to the invention, the accuracy and effectiveness of case recommendation are improved, and the reliability of the system under extreme disasters is improved.

The invention relates to a river levee dam break flood prediction method and device, and belongs to the technical field of flood prediction, and the method comprises the steps: predicting the future boundary data of a river channel through employing a historical rainfall-river channel boundary fitting algorithm according to the forecast rainfall of a weather bureau, and carrying out the prediction of the river levee dam break flood based on the future boundary data of the river channel and a one-dimensional hydrodynamic coupling mathematical model; predicting a future river section water level and a future river section flow; based on the future river section water level and the future river section flow, determining the water depth and the flow velocity of a coupling interface by combining a discontinuous interface algorithm; the water depth and the flow velocity of the coupling interface are used as boundary conditions to act on the two-dimensional hydrodynamic coupling mathematical model, and a momentum flux correction method is combined to predict the future ground flood level, so that the problems of unbalanced still water and unstable prediction during flood level prediction are solved, and the flood level prediction accuracy is improved.

The invention relates to the technical field of tailing pond infiltration line detection, and particularly discloses a direct-reading visual artificial intelligence detection device for a tailing pond infiltration line, two sides of a top plate are rotatably connected with supporting parts, the side surface of the top plate is fixedly connected with a gradienter, and the bottom of the top plate is fixedly connected with a blocking part. According to the direct-reading visual artificial intelligence detection device for the tailing pond infiltration line, the detection mechanism is arranged, the detection piece is lowered through the infiltration line detection pipe and can buzz after making contact with the water surface, and after receiving an alarm, detection personnel detect the situation through the video detection piece and directly read infiltration line burial depth data according to a scale cable; the accuracy of manual detection data of the tailing dam infiltration line is ensured, accurate comparison and analysis of online monitoring data of the infiltration line are facilitated, effective and accurate operation of an online monitoring device of the infiltration line is ensured, the stability of a dam body is kept, and dam break accidents are completely eradicated.