241 results about "Water dynamics" patented technology

The invention relates to the technical field of error correction, in particular to a water conservancy facility environment interference error correction method and device based on multi-dimensional data. The method comprises the following steps: collecting historical monitoring logs of water conservancy facilities, carrying out environmental disturbance event identification and multi-scale disturbance relevance mining, and constructing an environmental disturbance space-time relevance map; monitoring surrounding environment water monitoring parameters of the water conservancy facility, performing sequential response trend change analysis and dynamic response characteristic modeling, and constructing a facility environment personalized change response portrait; identifying a plurality of water body position monitoring data according to the surrounding environment water body monitoring parameters, and constructing a hydrodynamic full-field sensing graph; and performing nonlinear correlation analysis based on the hydrodynamic full-field perception graph and the personalized change response portrait of the facility environment, and constructing a digital twinborn model of the water conservancy facility under the water flowing condition. According to the invention, through dynamic error trend analysis and correction, the monitoring precision and monitoring stability of the water conservancy facility are improved.

The invention discloses a reservoir real-time scheduling simulation system based on a deep learning algorithm, and belongs to the technical field of intelligent water conservancy and artificial intelligence. Aiming at the problems of low prediction precision, poor multi-target coordination capability, weak coping uncertainty and the like of a traditional scheduling system, the system is designed to acquire hydrological, meteorological, water quality and engineering safety data through a multi-source data acquisition unit, and a multi-dimensional feature tensor is generated after preprocessing and fusion; the dispatching center server adopts an STGCN-LSTM mixed model to achieve high-precision prediction and uncertainty quantification of the water inflow process in the future 7-30 days, a reservoir hydrodynamic model and an MO-PPO algorithm are combined to complete multi-scene simulation and multi-target optimization decision, and an AF-DT mechanism dynamically adjusts the dispatching rule priority. According to the system, a sensing-decision-execution-feedback closed loop is constructed, the scheduling adaptive capacity and robustness are improved, the synergistic interaction of flood control, water supply, power generation and ecological protection is realized, and the system is suitable for real-time intelligent scheduling of large and medium reservoirs.

The invention provides a digital twin water conservancy hyper-fusion method for coupling multi-source data and an all-in-one machine, and relates to the technical field of intelligent water conservancy. By constructing a unified water conservancy spatio-temporal data link protocol, efficient fusion of multi-source heterogeneous data of hydrology, meteorology, engineering operation and the like is realized, and the problem of water conservancy system data islands is solved; a coupling distributed hydrological model and a hydrodynamic model are established, and real-time accurate simulation of the watershed hydrological process and the river channel hydrodynamic process is achieved; a multi-target dynamic weight reinforcement learning algorithm is adopted to optimize a water conservancy scheduling scheme, model parameters are dynamically corrected in real time through a time sequence error regression analysis model, and closed-loop adaptive optimization is achieved; according to the method, closed-loop cooperation of water conservancy data fusion, real-time accurate simulation, intelligent scheduling optimization and dynamic parameter self-correction is realized, and the real-time performance and accuracy of water conservancy intelligent decision making are remarkably improved.

The invention discloses a tuna pond culture strategy optimization method and system based on meteorological influence analysis, and the method comprises the steps: collecting regional meteorological data and pond culture monitoring data, and constructing a multi-modal pond ecological feature vector; establishing a weather-water body dynamic coupling model by using a space-time diagram neural network, and generating water body situation response prediction information; a breeding regulation and control strategy is made based on the prediction information, and strategy self-adaptive optimization is achieved through real-time monitoring data; evaluating the anti-disaster capability of the tuna after the meteorological influence is finished, screening high-quality germplasm resources by combining genetic analysis, and generating an anti-disaster breeding scheme. According to the method, full-chain optimization from meteorological early warning to culture regulation and control to genetic breeding is achieved, and the climate toughness and economic benefits of tuna pond culture are comprehensively improved.

The invention provides a tidal flat evolution prediction method and system based on a hybrid model, and relates to the field of dynamic geomorphology and artificial intelligence cross technology, and the method comprises the steps: constructing a tidal flat erosion and deposition evolution database under different scenes of a target coastal zone; constructing a landform prediction model through an artificial intelligence algorithm based on the database, and taking hydrodynamic characteristic data as input and seabed erosion and deposition variation as output; hybrid simulation is executed based on the physical mechanism model and the landform prediction model, and long-duration evolution prediction is realized by updating terrain boundary conditions through loop iteration; and the configuration service application module is used for receiving user input parameters through the interactive interface and outputting a visual result. According to the method, traditional hydrodynamic force-sediment-landform coupling calculation is decoupled into a physical mechanism and AI coordinated chain process, the calculation complexity is remarkably reduced, offline rapid calculation business of tidal flat evolution is achieved, and real-time technical support is provided for coastal zone planning and disaster prevention decision making.

The invention relates to a peak shaving power station downstream non-safe navigable water area identification method and system and a medium, and the method comprises the steps: building a peak shaving power station downstream river channel one-dimensional and two-dimensional coupling hydrodynamic mathematical model; determining a combination mode of a proposed condition and a water flow boundary condition of a typical peak regulation process of the downstream of the hydropower station; simulating and calculating downstream on-way hydrodynamic conditions of the power station under different peak shaving processes; calculating a downstream non-safe navigation index of the peak regulation power station; and identifying the downstream non-safe navigable water area of the peak shaving power station. According to the method, on one hand, the change condition of downstream hydrodynamic force of the peak regulation power station can be analyzed, on the other hand, the influence condition of the peak regulation process on downstream navigation conditions can be recognized, non-safe navigation water areas of the peak regulation power station in different discharge flow processes can be judged, and a research basis is provided for hub power generation and navigation scheduling of mountain rivers.

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 relates to the field of water engineering, and discloses a method for installing and positioning a prefabricated part under a complex hydrological condition, which comprises the following steps of: arranging a sensor network on the surface of the part, and establishing an initial reconstruction model of strain-hydrodynamic load mapping based on finite element analysis; acquiring sensor strain data in real time, and synchronously acquiring component pose information of an external positioning system; real-time hydrodynamic disturbance is calculated through the initial model, and sensor health diagnosis is carried out in combination with a dynamic threshold value method; the extended Kalman filter fuses the pose and disturbance data, and model parameters are updated online to generate a calibration model; and on the basis of calibration model output and state estimation, a feedforward-feedback composite control instruction is generated to drive an execution mechanism to adjust the pose. Through an online calibration model and a composite control architecture, and in combination with optimal distribution of a redundant execution mechanism, real-time offset of hydrodynamic disturbance and millimeter-level pose regulation are realized, and the technical bottlenecks of low precision and poor adaptability of a traditional method are broken through.

The invention relates to the technical field of bamboo forest ecological environment monitoring, in particular to a bamboo forest ecological environment collaborative observation method based on multi-source Internet of Things sensing, and the method comprises the steps: synchronously collecting a multi-source collaborative observation parameter set of a bamboo forest slope through an Internet of Things sensor network, and then constructing a point-surface scale fusion bamboo forest moisture dynamic model; correcting evapotranspiration point cluster data by using a random forest gradient lifting algorithm to generate terrain weighted evapotranspiration, aggregating runoff data according to terrain weight to obtain a total amount of runoff sub-regions, then executing dynamic water balance constraint calculation, optimizing infiltration capacity in combination with a variation assimilation algorithm, redistributing infiltration capacity space proportion according to soil hydraulic conductivity when a residual error exceeds a threshold value, and calculating the total amount of the runoff sub-regions. Finally, according to the residual space distribution thermodynamic diagram, the evapotranspiration point cluster is migrated to the micro-topography representative area, and observation network adaptive optimization is achieved, the problems that in the prior art, the data scale is disjointed, the observation precision is insufficient, and the network is difficult to adapt to change are solved, and the bamboo forest ecological observation precision and reliability are improved.

The invention discloses a wave-current combined simulation system and method in a low-pressure environment, and relates to the technical field of underwater vehicle hydrodynamic model tests. The defects that in the prior art, sealing and strength are difficult to guarantee in a low-air-pressure environment, and accurate flow velocity and shear gradient control of a multi-layer flow channel cannot be achieved are overcome. According to the technical scheme, the device comprises a low-pressure pool, a plurality of layers of layered water inlet galleries, a plurality of layers of layered water outlet galleries, a rectifying wall, a rectifying baffle, a flow guide grid, a wave absorbing bank, an in-cabin rocking plate type wave maker, a plurality of bottom flow making pump flow making systems, an electric butterfly valve, a high-voltage frequency conversion cabinet, a three-phase asynchronous motor, a gear box, an impeller shaft system and the like. All the devices work cooperatively, and accurate coupling simulation of a multi-layer flow field and high sea condition waves under low air pressure is achieved. The device is suitable for wave-current combined hydrodynamic characteristic simulation and test research of deep-sea navigation bodies and ocean engineering equipment in a low-pressure environment.

The invention discloses a device for simulating influence of ditch cleaning ice cover evolution on hydrodynamic parameters and an application method thereof, and relates to the technical field of ice water dynamics and hydraulic engineering experiments. The device comprises a low-level water tank, a high-level water tank, a centrifugal pump, a flow valve, a water tank, a steady-flow perforated plate, a ditch cleaning ice cover simulation device, a first water level control grid plate, a second water level control grid plate and a flow field measurement system. According to the invention, three key parameters of ditch cleaning length, ice cover submerging water depth and roughness of the bottom of the ice cover are independently regulated and controlled, and non-contact high-precision measurement is carried out by means of a PIV technology, so that systematic and refined research on hydrodynamic parameters of an ice cover ditch cleaning area is realized. According to the method, researchers can safely and systematically research the influence of a single variable on the ice cover ditch cleaning water power at low cost, and the fundamental bottleneck of traditional field measurement in the research is solved.

The invention discloses a flood process runoff monitoring method coupled with satellite remote sensing and hydrodynamics. The flood process runoff monitoring method comprises the following steps that unmanned aerial vehicle complete river topography measurement is carried out; river upstream and downstream section hydraulic parameters are obtained; constructing a digital river channel section; batch extraction of satellite remote sensing water surface width; flow calculation parameters are obtained based on the digital river section and the water surface width data; performing remote sensing inversion on the roughness of the complete riverway; and section flow monitoring and historical data inversion. A section of complete river channel is determined as a basic research unit, flow calculation precision is remarkably improved through multi-section synchronous monitoring in combination with river channel slope and roughness change dynamically captured in real time, the flowing process of water flow in the complete river channel is finely described, and the flow calculation precision is improved. The method provides long-sequence and high-reliability flow data for parameter calibration and result verification of a hydrological model, is particularly suitable for describing the flow condition when flood comes, and enables the flow condition to be closer to reality.

The invention provides a historical flood inundation dynamic reconstruction method and system based on deep learning, and relates to the technical field of flood simulation, and the method comprises the steps: obtaining a standardized historical flood data set; positioning P terrain cavity deficiency; matching and multiplexing P adaptive filling models in a terrain filling model library according to the P missing feature vectors; carrying out multi-thread parallelization of P terrain cavity deletion; adopting the P corrected terrain structures to carry out pixel-level replacement of P terrain cavity missing to obtain corrected DEM data; and after a two-dimensional hydrodynamic model is constructed based on the corrected DEM data, a hydrodynamic boundary control set is set to drive the two-dimensional hydrodynamic model to execute flood simulation, and a historical flood dynamic evolution process is output. According to the flood simulation method and device, the technical problem that the flood dynamic reconstruction accuracy is affected due to the fact that the flood simulation accuracy is limited due to the fact that topographic data are incomplete and the simulation generalization ability in different areas is insufficient in the prior art is solved, and the flood simulation accuracy is improved.

The invention provides an intelligent lake and reservoir water quality forecasting method and system based on physical constraint guidance and a medium. The method comprises the following steps: constructing and verifying a hydrodynamic water quality mechanism model; constructing a deep learning water quality intelligent model: preprocessing the historical hydrological water quality monitoring data to obtain a Transform-based deep learning water quality intelligent model and an input data set; constructing a physical constraint loss function based on a simulation result of the hydrodynamic water quality mechanism model subjected to calibration verification; using an input data set as a training set, taking minimization of a total loss function as a target, training the deep learning water quality intelligent model, and using the trained model for lake and reservoir water quality forecasting. According to the method, the physical mechanism is deeply embedded into the training process of the data-driven model in a differential constraint form, so that the prediction result strictly follows the physical law of pollutant migration and transformation while conforming to observation data, and the problem that the prediction result of a pure data-driven model violates physical common knowledge is effectively solved.

The invention discloses a flood inundation range dynamic simulation method and system based on multi-source data fusion. The method comprises the following steps: S1, collecting multi-source original data of a to-be-simulated target drainage basin; s2, extracting an initial submerging range grid according to the multi-source original data; s3, according to the initial submerging range grid, generating a river channel-beach area coupled section terrain file; s4, obtaining the dynamic water level process of each downstream section according to the section topographic file and the weather forecast rainfall field; and S5, obtaining a dynamic simulation result of the flood inundation range according to the dynamic water level process. According to the invention, through continuous driving of the distributed hydrological model and the one-dimensional hydrodynamic model, full-chain simulation from rainfall forecast to submerging dynamic state is realized, so that the submerging range can be updated in real time along with meteorological conditions and riverway water levels.

The invention relates to the field of disaster prevention and management, and particularly provides an intelligent decision-making method and device for realizing flood simulation prevention in combination with Cesium, and the method comprises the following steps: S1, geographic data access; s2, realizing real-time monitoring and analysis of hydrological conditions; s3, flood simulation model construction comprises hydrodynamic model construction, model parameter setting and optimization, and mechanism real-time updating; s4, processing physical interaction of the water flow by a Chaos physical engine of Unreal Engine, and associating physical data of Chaos through modular logic; s5, integrating an LSTM time sequence prediction model and combining with hydrological real-time rainfall to realize a flood routing trend; s6, displaying key disaster areas and disaster water level conditions by HeatMap; and S7, identifying a nearby refuge point location, and scientifically and reasonably arranging an emergency path. Compared with the prior art, intelligent decision management can be provided for pre-disaster simulation prevention and post-disaster rescue recovery.

The invention relates to the technical field of water environment monitoring and water ecological protection, solves the technical problem that hydrology, water quality, vegetation and bottom mud monitoring are mutually dispersed and are difficult to correspond in the prior art, and particularly relates to a lakeside microenvironment composite monitoring pile and an ecological disturbance evaluation method. The composite monitoring piles sequentially comprise an overwater area, a variable water level zone monitoring area and an underwater area in the vertical direction, the bottoms of the composite monitoring piles are fixed to bottom mud, the multiple composite monitoring piles are arranged according to the water depth gradient of 0-20 cm, 20-50 cm and 50-100 cm, a hydrodynamic force disturbance index and a microenvironment response index are established by comparing base line and disturbance working condition monitoring results, a composite ecological disturbance index is established, and the water level zone monitoring area and the water level zone monitoring area are located in the bottom mud. The method is used for quantitatively evaluating lakeside disturbance intensity and engineering measure effects. According to the method, quantitative and graded evaluation of the ecological disturbance degree of the lakeside zone is realized, and a scientific basis is provided for lakeside zone revetment form optimization, ecological restoration measure arrangement and water function zone management.

The invention discloses a lake pollution traceability analysis method based on multi-source data assimilation and reverse diffusion, and relates to water pollution traceability analys.The lake pollution traceability analysis method comprises the steps that chemical pollution is monitored at the downstream of a lake, monitoring data are imported into a hydrodynamic force-water quality model after Kalman filtering, and spatial and temporal distribution data of pollutants in a water body are obtained; pollution source inversion is carried out based on a differential evolution Markov chain Monte Carlo method, and pollution source parameters are obtained; forward simulation is carried out, a flow velocity field and water depth are solved through a hydrodynamic force-water quality model, then a pollutant transport model is generated, pollution source parameters are used as input, a finite volume method discrete control equation is used based on the pollutant transport model to predict pollutant concentration space-time evolution, and pollution duration under natural attenuation is evaluated; and comparing real-time monitoring data with an expected effect, and evaluating a pollution traceability analysis effect. Pollution source positioning errors are reduced, pollution contribution rate calculation accuracy is improved, traceability efficiency is improved, the risk of excessive reagents is avoided, and treatment cost is reduced.

The invention discloses a Taylor flow two-phase volume fraction prediction method based on CFD and machine learning, and belongs to the field of hydrodynamics. The method aims at solving the problems that traditional CFD is low in efficiency and weak in generalization, and pure machine learning lacks explanatory and physical consistency. According to the method, a mixed CFD-ML framework integrating an interFoam solver of OpenFOAM and machine learning is constructed. The method comprises the steps that firstly, a multi-working-condition calculation example is established based on OpenFOAM, and a training data set containing velocity fields Ux and Uy and a liquid phase volume fraction field alpha. Water is generated through interFoam; training a fourier neural operator (FNO)-based model by using a training solver to obtain an optimal model; and finally, loading the model by using a prediction loop solver, and quickly predicting the volume fraction field of the next time step in CFD time marching. The method improves the prediction efficiency and precision, guarantees the physical consistency, is suitable for the fields of ocean engineering, oil and gas transmission and the like, and can be expanded to a multiphase flow scene.

The invention belongs to ecological environment engineering, and particularly relates to a river and lake wetland zoning and classifying ecological water demand fine accounting method, which comprises the following steps of S1, performing zoning and classifying on a river and lake wetland of a research area; s2, establishing a space-time coupling hydrodynamic model based on a partition classification relationship; s3, constructing a multi-factor ecological response model, and calculating an ecological suitability index of each partition; s4, establishing a multi-objective optimization model, and performing optimization solution on the ecological water demand of the partition by combining ecological benefits, water balance and process smoothness objectives; and S5, performing robust correction on an optimization result by adopting an uncertainty analysis method to obtain a final ecological water demand distribution result. By establishing a river and lake wetland partition classification spatial database based on digital elevation, river network distribution, land utilization and ecological attribute information, fine description and dynamic association of different ecological functional areas are realized, and the effects of ecological process differentiation characterization and remarkable improvement of water demand accounting precision are obtained.

The present disclosure relates to the technical field of model construction, and provides a river water dynamics model construction method based on multi-source remote sensing, which comprises the following steps: acquiring a river remote sensing image to obtain a water edge line, acquiring water level data by means of an altimeter satellite, and giving an elevation value to a water edge line corresponding point according to the water edge line and the water level data; for a straight river section, a value is taken according to a specific rule, and for a curved river section, the value is determined according to linear fitting of multiple elevation measuring point values on a river section; based on the elevation values of the water edge lines of the straight and curved river sections, a river terrain digital raster model is further constructed by interpolation along the water edge line, the river water dynamics model is constructed by using the river terrain digital raster model, the simulation effect of the water dynamics model is determined by comparing the water level consistency or the water surface vector form consistency, and the calibration and verification of the river water dynamics model are realized. The present disclosure realizes accurate simulation of the river water dynamics process. The present disclosure can reduce the cost of model parameter acquisition.

The invention belongs to the technical field of hydrodynamics, and relates to a subsurface flow accurate measurement method and system based on an acoustic Doppler flow velocity profiler. The method comprises the following steps: measuring a target water area by using an acoustic Doppler current profiler; extracting at least one boundary feature parameter at the measurement point; constructing a physical-data fusion model and carrying out pre-training; inputting effective flow velocity data located above the measurement blind area in the original data of the flow velocity profile and the boundary characteristic parameters into a pre-trained physical-data fusion model; and outputting the subsurface flow velocity distribution in the measurement blind area and the key statistic and confidence interval of the subsurface flow velocity distribution. According to the method, the respective defects of an existing physical model and an existing data driving model can be overcome, a subsurface flow accurate measurement method integrating physical interpretability and environment adaptability is provided, a traceable and verifiable model training and evaluation benchmark is provided, and the subsurface flow measurement accuracy in a complex environment is remarkably improved.

The invention discloses a surface flood rapid calculation method based on a Fourier neural operator, and provides an urban flood modeling and numerical calculation method fusing a two-dimensional hydrodynamic model and a physical constraint Fourier neural operator. According to the method, a multi-scale feature mapping and physical constraint mechanism is introduced under a framework of solving a surface flood evolution process by a traditional shallow water equation, and nonlinear mapping from a low-resolution simulation result and multi-source environment driving data to a high-resolution flood response field is realized, so that a high-resolution flood response field is obtained on the premise of ensuring physical rule constraints. According to the invention, high-precision and rapid prediction of the urban flood process is realized.

The invention provides a river channel flow field state determination method and device, equipment and a storage medium, and the method comprises the steps: sampling river channel model parameters based on a hydrodynamic control equation to generate a hydrodynamic response sample set covering different feature combinations; and screening abnormal samples in the sample set to obtain an effective data set. According to statistical characteristics and a physical parameter prior range of an effective data set, static attributes and dynamic states of a river channel are coded into dimensionality-fixed structured representation, and a physical enhanced agent model taking the representation as input is constructed. A joint optimization target training model containing a data fitting item and a hydrodynamic control equation physical constraint item is adopted, target river channel entity attributes are converted into matched target structured representation through a space adaptation mechanism, the target structured representation is input into the trained model for flow field deduction, and a flow field state prediction result of the target river channel at the future moment is obtained. By adopting the method, the efficiency, accuracy and suitability of flow field prediction can be improved.

The invention provides a hydrodynamic model-based mountain river flood diversion tunnel line and scale optimization design method, which comprises the following steps of: constructing a one-dimensional hydrodynamic mathematical model of a research area drainage basin by adopting MIKE11 software, and constructing a one-dimensional hydrodynamic model of the research area drainage basin according to the one-dimensional hydrodynamic mathematical model of the drainage basin, boundary conditions and calibrated comprehensive roughness; and calculating designed flood water surface lines of different frequencies of the urban section. According to the actual situation of a city, aiming at urban flood causes and main problems existing in a current flood control system, engineering measure schemes such as flood control reservoir construction, beach retreating and river returning, river regulation, embankment heightening and flood diversion channel building are proposed, and a flood diversion tunnel route and planning optimization research is developed on the basis of a hydrodynamic model. Numerical simulation of flood disasters is completed by means of the modern information technology, a complete disaster prevention and control system is established for achieving the purposes of scientization, high efficiency and automation of disaster prevention and relief decision, the urban flood prevention capacity can be comprehensively improved, and the life and property safety of the masses is guaranteed.

The invention belongs to the technical field of reservoir related data correlation analysis, and discloses a reservoir capacity distribution characteristic coefficient and flood control capacity correlation data analysis method. The method comprises the following steps: S1, based on a sensor network, collecting reservoir related data in real time to obtain a reservoir data set; s2, quantifying reservoir capacity characteristics based on the reservoir data set; s3, correlating reservoir capacity characteristic data with flood control capability data through calculation; s4, a hydrodynamic equation is introduced to correct the calculation deviation; s5, quantitatively evaluating the influence intensity of the storage capacity feature data; s6, real-time risk early warning diagnosis is carried out according to the flood control evaluation value; in general, the flood risk prediction method has the remarkable advantages of being high in flood risk prediction accuracy, high in auxiliary decision-making capacity, good in sustainable use economical efficiency and the like.

The invention discloses a bay hydrodynamic prediction method based on a hybrid Fourier neural architecture, and belongs to the technical field of hydrodynamic prediction, the method comprises the steps of data conversion, data preprocessing, topological relation construction, feature extraction and fusion, model construction, training and prediction, and the like, the data format is converted through a modified trim2nc data packet, and the data format of the trim2nc data packet is converted into the data format of the trim2nc data packet; performing preprocessing to obtain static and dynamic feature data sets; constructing a grid topological relation by using a Delaunay triangulation algorithm; space and time features are extracted through a graph neural network and a time convolutional network respectively and fused; frequency domain calculation is carried out in combination with a Fourier neural operator network with the irregular geometric boundary processing capability, physical knowledge is coupled to define a loss function training model, and finally rapid and accurate prediction of the gulf hydrodynamic force is achieved. According to the method, the problems of high calculation cost and low efficiency of a traditional hydrodynamic model are solved, the prediction precision and efficiency are considered, and a reliable basis can be provided for bay water environment management and planning.

The invention provides a high-fidelity generalization method and system for plain river network water flow simulation, and relates to the technical field of model simulation. The method comprises the steps that a node river network is constructed, constructing a physical river network topological structure comprising a main river channel node, a river reach, a regulation and storage node and a virtual river reach; a dynamic parameter configuration step: configuring hydraulic parameters for the section in the physical river network topological structure; a boundary coupling step: distributing water catchment unit runoff obtained by calculation of the hydrological model to corresponding regulation and storage nodes as boundary input conditions; and a simulation execution step: performing hydrodynamic simulation calculation based on the constructed physical river network topological structure, the configured hydraulic parameters and the distributed boundary input conditions. Through a high-low water level dynamic parameter method, a hydrodynamic model parameter calibration method is optimized, especially for rivers with large water level fluctuation amplitude, and the accuracy of simulation results is ensured.

The invention discloses a multi-dimensional comprehensive prediction and characterization method and system for water-rich sandy gravel stratum tunnel water gushing, and relates to the technical field of tunnel engineering.The method comprises the steps that geological survey is conducted on a water-rich sandy gravel stratum tunnel construction area, geological data are obtained, multiple monitoring sensors are arranged, and hydrodynamics and hydrochemistry data are collected in real time; building physical models of the tunnel area, wherein the physical models comprise a three-dimensional geologic model, a hydrodynamic model and a hydrochemical model; based on the hydrodynamic model and the hydrochemical model, performing dynamic water gushing prediction according to hydrodynamic data and hydrochemical data acquired in real time, and outputting predicted water gushing intensity, spatial distribution and time change trend of a next time step; and the prediction data are mapped into a three-dimensional geologic model, a flow field vector diagram and a concentration distribution heat map are generated, and a prediction result is compared with monitoring data of a next time step, so that model parameters are dynamically adjusted and updated. According to the invention, high-precision dynamic water gushing prediction can be realized.

The application provides a water temperature monitoring and extraction simulation device based on coal mine geothermal energy, and belongs to the technical field of geothermal energy. The device comprises a tank body, an inner cavity is arranged in the tank body, three isolation plates are fixedly connected in the inner cavity, the inner cavity is divided into three cavities by the isolation plates, a placing box with an open top is arranged in each cavity, prefabricated samples are placed in the placing boxes, a plurality of temperature sensors are prearranged in the prefabricated samples, and a vibration assembly is arranged outside the tank body. The isolation plates, the multiple pressure applying assemblies and the elastic rods with different heights are cooperated, so that the multiple stress environments of the coal mines with different depths can be simulated at the same time, the actual stratum differences are better matched, the water penetration is actively controlled by the lifting assembly, the underground water dynamic infiltration process is accurately restored, the static water supplement is avoided to be disconnected with the actual situation, the sample crack water is uniformly distributed by the vibration assembly through vibration, the local water accumulation or vacancy is prevented, and the accuracy and reliability of the water temperature monitoring data are improved.