1876 results about "Submarine" patented technology

The invention belongs to the field of submarine routing planning, particularly relates to a pipeline routing line selection method and system based on a path planning algorithm and analytic hierarchy process, and aims to improve the routing line selection efficiency and precision and reduce the routing risk in the pipeline routing line selection process. The method comprises the following steps: establishing an evaluation sample matrix X based on measured value data of evaluation indexes, and converting pixel points of a target sea area topographic map into nodes of a two-dimensional matrix to obtain a grid obstacle map; establishing a submarine pipeline routing risk quantitative evaluation model; converting the sea area topographic map into a risk level grey-scale map through the risk quantitative evaluation model of the submarine pipeline; and carrying out route planning through a route planning algorithm based on the grid obstacle map, and finding a route with the minimum accumulated gray value in the target sea area risk level gray-scale map through a greedy algorithm to serve as a final route. According to the method, risk parameters are taken into consideration for the generated path, and finally, the obtained route is a routing path with small length and low overall risk.

The invention discloses a submarine scoured pipeline stability early warning method based on artificial intelligence, and relates to the technical field of submarine pipeline protection, and the method comprises the steps: collecting and sorting submarine pipeline historical reconnaissance data and monitoring data of a target region; and constructing a seabed-submarine pipeline local fine three-dimensional hydrodynamic-sediment numerical model on the basis of a solution Navier-Stokes equation and a sediment transportation model. According to the method, the historical reconnaissance data, the monitoring data and the numerical model result are integrated, the coupling effect of various factors can be comprehensively considered, then the dynamic characteristics of seabed scouring are more comprehensively captured, key scouring factors influencing the stability of the pipeline are more accurately recognized, and meanwhile, the scouring process and result simulated by the numerical model are combined, so that the stability of the pipeline is improved. According to the method, the stress distribution and deformation conditions of the pipeline under different scour depths can be analyzed more accurately, then an early warning signal is sent out in advance, the risk that the pipeline is damaged due to scour is effectively reduced, and the reliability and accuracy of early warning are improved.

The invention discloses a submarine pipeline stability discrimination method based on submarine scour mechanism analysis, and relates to the technical field of submarine facility protection, basic data of a target sea area are obtained, and the basic data comprise geological information of an area where a submarine pipeline is located, hydrological information of a sea area near the pipeline and pipeline information; performing feature analysis on the basic data of the target sea area, and extracting feature data related to water flow scouring, wave scouring and soil particle movement; according to the method, the risk area which is easily influenced by scouring around the pipeline is accurately identified through seabed scouring mechanism analysis, and then key monitoring and early warning are performed on the risk area, so that protection measures are strengthened in a targeted manner, and the influence of scouring on the stability of the pipeline is dynamically evaluated through continuous monitoring and analysis; the problems of pipeline deformation and stress concentration caused by scouring can be found in time, a maintenance strategy is adjusted according to the problems, the pertinence of safety protection is improved, resources can be effectively saved, and the maintenance cost is reduced.

The invention discloses a submarine pipeline state early warning method and system based on scour-vibration coupling sensing, and the method comprises the steps: obtaining the historical marine environment information of a target submarine pipeline region, laying a monitoring sensor array according to the historical marine environment information, collecting multi-source monitoring data, and carrying out the preprocessing of the multi-source monitoring data, thereby forming a multi-source monitoring data set. And constructing a multi-physical field coupling analysis model, inputting the data set into the model to analyze the response condition of the pipeline in the current seabed environment, and obtaining pipeline response simulation information. And analyzing resonance influence caused by environmental scouring in different sections, generating resonance derivative characteristics, and constructing pipeline multi-modal fusion characteristics in combination with monitoring data. Predicting the future response state of the pipeline through the submarine pipeline state analysis model, and carrying out risk early warning prompt; meanwhile, the fatigue life of each section is analyzed based on resonance derivative characteristics, fatigue-prone sections are identified, and maintenance suggestions are generated and pushed. Therefore, the accuracy and timeliness of sensing the state of the submarine pipeline are improved, and the early warning intelligence of the submarine pipeline is effectively improved.

The invention relates to the technical field of ocean exploration, in particular to a non-buried submarine pipeline identification method and system based on multi-beam point clouds, and the method comprises the steps: obtaining three-dimensional point cloud data of a submarine pipeline region, and carrying out the preprocessing of the obtained point cloud data; performing neighborhood construction based on the preprocessed point cloud data, setting a mask attention mechanism according to a neighborhood structure, performing geometric coding and feature enhancement by using an output result of the mask attention mechanism, performing decoding operation on the enhanced features, recovering feature representation of the complete point cloud, and performing suspended span height calculation and verification based on a segmentation result. According to the method, a decoding strategy combining reverse distance weighted interpolation and jump connection is adopted, enhanced features are accurately propagated to the original point cloud, the seabed datum plane is fitted through the reverse distance weighted interpolation, and the high-risk suspended cross area can be rapidly positioned.

The invention discloses a seabed sand excavation pit slope change monitoring method, system and device and a medium. The method comprises the steps that a seabed pipeline distribution diagram for generating a target seabed sand excavation area is formulated; generating a plurality of side slope units in the target seabed sand excavation area according to the collected side slope topographic data; taking each side slope unit as a basic unit, obtaining a side slope disaster susceptibility evaluation index and a side slope disaster risk evaluation index, and carrying out risk calculation to obtain a corresponding disaster risk evaluation result; acquiring position data of each side slope unit, associating the submarine pipeline distribution map with the side slope units based on the position data of each side slope unit and the corresponding disaster risk evaluation result, and generating a side slope pipeline risk distribution model; based on the slope topographic data and disaster risk evaluation results of each slope unit in different data acquisition periods, obtaining a slope change trend of the target seabed sand excavation area; the effect of improving the change monitoring efficiency of the seabed sand excavation pit slope is achieved.

The invention discloses a seabed target sonar detection method based on an adversarial network, and the method comprises the steps: S1, collecting deep sea sonar original data, and carrying out the preprocessing of the data, and obtaining a standardized sonar tensor; s2, taking the standardized sonar tensor as training input, and training an improved StyleGAN-3 model in combination with an environmental parameter vector; s3, calling the improved StyleGAN-3 model, and outputting a weak target feature tensor; s4, constructing a sonar detection network; s5, outputting an optimal detection parameter set; and S6, loading the optimal detection parameter set to the sonar detection network, performing target judgment on the weak target feature tensor, and outputting a target confidence value, a three-dimensional space positioning result and a target motion track. Compared with a traditional method, the method has the advantages that in a deep sea scene, the positioning error and the target trajectory loss rate are greatly reduced, the method has excellent online tracking and dynamic situation awareness capabilities, and a solid technical support is provided for ocean monitoring, security and emergency command application.

The invention discloses an energy consumption optimization path planning method for an underwater robot. According to the method, an ocean current model is established by using a Navier-Stokes equation, and complex water flow in the ocean is simulated; a mountain peak model is used for simulating complex submarine topography, and a sphere model is used for simulating random obstacles in the ocean; the outer layer of the path planner adopts a particle swarm optimization algorithm, the inner layer of the path planner adopts a sequential quadratic programming algorithm, and the optimal speed of each section of path can be obtained while path points are obtained; fitting path points by using a B-spline curve to generate a smooth path; and a special fitness function calculation mode is adopted, and a re-planning strategy is combined, so that the calculation efficiency of the algorithm is improved. According to the method, the optimal navigation speed of the robot in different environments can be calculated, the energy consumption of the planned path is reduced on the basis of ensuring the navigation time and safety of the robot, and the efficiency and robustness of path planning are effectively improved through a multi-algorithm combined double-layer path planner and a dynamic re-planning mechanism.

The invention discloses a marine surveying and mapping system based on deepwater exploration robot intelligent navigation, and belongs to the technical field of marine surveying and mapping. Comprising a data acquisition module for synchronously acquiring navigation positioning data and submarine topography data through multi-source navigation equipment carried by a deepwater detection robot and submarine measurement equipment; the navigation fusion module is used for realizing self-adaptive fusion of multi-source data and outputting initial pose estimation; the quality control module is used for carrying out quality evaluation and abnormity identification on the real-time surveying and mapping data; the path planning module is used for planning an optimal surveying and mapping path in real time and carrying out online adjustment according to the re-measurement requirement of the quality control module; the fault-tolerant control module is used for realizing multi-level navigation source fault diagnosis, starting a degraded navigation strategy when navigation is abnormal or fails, and ensuring that basic navigation and surveying and mapping functions can still be maintained; and the topographic surveying and mapping module is used for compensating and splicing submarine topographic data in real time by using the pose information provided by the navigation fusion module.

The invention discloses a seabed sonar image processing method based on semantic segmentation. The method comprises the following steps: S1, obtaining preprocessed sonar image blocks; s2, generating a submarine landform boundary priori map corresponding to the preprocessed sonar image blocks pixel by pixel; s3, an improved U-Net double-branch semantic segmentation network is constructed, the improved U-Net double-branch semantic segmentation network comprises a semantic branch and a boundary branch, and a landform mutual feedback gating module is configured in each scale jumper connection layer; s4, obtaining a fusion feature map; s5, deploying to the autonomous underwater vehicle to form an onboard reasoning model; and S6, performing online semantic segmentation reasoning on the preprocessed sonar image block acquired in real time by using the onboard reasoning model, and outputting a semantic category diagram and a boundary vector diagram corresponding to the preprocessed sonar image block. According to the method, the average mIoU index of the model is improved in a small-target and multi-category hybrid scene.

The invention relates to the field of civil engineering structure health monitoring, in particular to a subsea tunnel damage intelligent monitoring and identification method based on acousto-optic collaborative perception. The method sequentially comprises the steps of deploying a three-dimensional acousto-optic sensing network, actively detecting sound waves, reconstructing a local sound velocity distribution cloud picture, identifying a sound velocity abnormal region, performing optical fiber response focusing sampling and establishing an intelligent damage diagnosis model. According to the method, the three-dimensional acoustic array and the distributed optical fiber grid are simultaneously deployed in the subsea tunnel structure, functional complementation is realized between the three-dimensional acoustic array and the distributed optical fiber grid, seamless cooperative sensing of crack coarse positioning and strain fine positioning is further realized, acoustic active detection, trigger type optical fiber high-frequency sampling and a temperature-strain decoupling algorithm are adopted, and the positioning precision of the subsea tunnel structure is improved. Seawater noise and thermal expansion interference are effectively eliminated, 'dry cracks' and'water seepage cracks' are accurately distinguished, real-time monitoring is carried out on a subsea tunnel structure, whole-process identification of micro-damage-expansion-failure is achieved, and an active early warning mechanism is established.

The invention relates to the technical field of earthquake prediction, in particular to a submarine seismic oscillation prediction method and device based on earthquake exploration, and the method comprises the following steps: selecting a monitoring region, collecting the submarine topographic data of the monitoring region, and drawing a topographic map; selecting a plurality of monitoring points according to the topographic map; geomagnetic field information, electric wave information, micro-seismic activity information and seabed deformation information of each monitoring point are collected and recorded; converting the collected information into acoustic signals and transmitting the acoustic signals to a sea surface buoy, and converting the acoustic signals into electric signals by the sea surface buoy and transmitting the electric signals to a ground data center; by optimizing site selection of monitoring points, integrating geomagnetic-electric wave-microseismic-deformation multi-source data, realizing high-efficiency data transmission by using an acoustic-electric staged communication chain, and finally realizing early recognition of earthquake precursor in combination with threshold analysis, the method can significantly improve the coverage range, data precision and early warning timeliness of seafloor earthquake monitoring, and has good application prospects. And a technical support is provided for marine geological disaster prevention and control.

The invention relates to the technical field of oil well yield prediction, in particular to an electric submersible pump well yield prediction method fusing an electric submersible pump mechanism and a large language model, and the method comprises the steps: firstly collecting historical production data of an oil field, carrying out the preprocessing, and dividing the data into a training set, a verification set and a test set; according to attributes of all wells in the electric pump well attribute database, storage and transportation mechanism knowledge is established and represented, and a representation result is further refined to obtain an electric pump well mechanism model; inputting attribute parameters of a single well in the gathering and transportation pipe network into a pre-trained large language model to construct a large language model fusing mechanism knowledge, and sequentially training and evaluating; and finally, inputting the data of the test set into a big language model fused with mechanism knowledge for prediction to obtain a prediction result of the yield of each electric pump well in the electric pump well pipe network, introducing reprogramming and text mapping on the basis of the big language model, converting a time sequence prediction task into a language task, and finally obtaining a prediction result of the yield of each electric pump well in the electric pump well pipe network. And a large language model is successfully applied to the field of oil well yield prediction.

The invention discloses a multi-field sensing fusion deep sea geological environment dynamic monitoring system and an application method. The system comprises a buoy measuring platform, a multi-beam sounding system, a high-precision marine gravimeter, an external camera, a GPS, a data acquisition and transmission control unit and a power supply system. By designing a modularized and integrated multi-sensor buoy platform, various sensors are fused and integrated. A plurality of sensors are connected to the data acquisition control terminal, the steps of sensor calibration, data synchronization and clock calibration, correction and compensation, data acquisition, real-time processing, fine post-processing, data transmission and the like are completed, and multi-sensor collaborative operation is realized, so that submarine topography and ocean gravity data of a deep sea ditch area are synchronously acquired in real time; and thus, diving erosion information experienced by the area can be accurately monitored. The method can provide important support for submarine topography and landform detection and application and marine geographic information system construction, and has application value in the aspects of geological disaster early warning, resource development and the like.

The invention discloses a submarine floating icebreaking load measurement test device and a submarine floating icebreaking load measurement test method. The submarine floating icebreaking load measurement test device comprises a test box, an ice block clamp, a moving assembly, a lifting assembly, an angle adjusting assembly and an observation assembly. Wherein the ice block clamp, the moving assembly, the lifting assembly and the angle adjusting assembly are all arranged in the test box, the ice block clamp is used for fixing ice blocks, the moving assembly is used for driving the submarine model to move in the horizontal direction, the lifting assembly is used for driving the submarine model to move in the vertical direction, and the angle adjusting assembly is used for adjusting the pitch angle of the submarine model. The observation assembly is used for recording the stress condition and the water outlet posture of the submarine model. According to the test device, the position and posture of the submarine model can be adjusted through the moving assembly, the lifting assembly and the angle adjusting assembly, so that different icebreaking conditions are simulated; and the icebreaking process of the submarine model is recorded through a force sensor and a camera. The invention relates to the field of submarine icebreaking test research.

The invention belongs to the technical field of marine seismic exploration, and discloses a submarine node laying device and laying method based on a wireless underwater robot. The seabed node laying device comprises a node laying control unit arranged on a node ship, a node matrix retracting and releasing unit arranged on the node ship, a node matrix used for filling an OBN and conveying the OBN to an underwater specified depth, and at least two wireless underwater robots used for carrying the OBN underwater and completing OBN laying. The node matrix is connected with the node laying control unit and a power supply system of the node ship through a multifunctional cable so as to realize data communication and power transmission; the node matrix is connected with the node matrix retracting and releasing unit through a steel cable so as to achieve underwater lifting and releasing of the node matrix. And the wireless underwater robot realizes data communication with the node matrix in a radio communication mode. By means of the device, the operation mode that double-node matrix alternate operation is adopted, and multiple wireless underwater robots throw nodes is adopted, and the OBN laying speed can be increased in a multiplied mode.

The invention discloses an ocean induced polarization and natural potential combined acquisition device and a data processing method, and solves the technical problem that the sulfide ore form cannot be accurately represented in the prior art. The system comprises a first underwater autonomous robot and a second underwater autonomous robot, the first underwater autonomous robot is provided with an induced polarization emission device, and the second underwater autonomous robot is provided with a natural potential acquisition device; the induced polarization emission device comprises an induced polarization control bin, a first watertight cable, an emission end positive pole and an emission end negative pole, and the natural potential acquisition equipment comprises a natural potential acquisition bin, a second watertight cable and a plurality of pairs of Ag / AgCl non-polarized electrodes. According to the method, the distribution characteristics of submarine sulfides can be more accurately explained, the multiplicity of solutions is reduced, and the exploration accuracy and reliability are improved.

The invention discloses a detection method of an ocean magnetic field sensor based on a diamond NV color center. The detection method comprises the following steps: S1, calibrating a base line; s2, alternately measuring fluorescence between two single quantum resonance frequencies, and obtaining a difference to realize DQ reading; s3, three-axis compensation current is adjusted based on closed-loop control, and the NV working point is maintained at zero magnetization bias; s4, obtaining background magnetic field change through digital demodulation and adaptive filtering; and S5, calculating a gradient based on the spatial difference of the multi-point light spots, judging the existence and trajectory of the underwater vehicle in combination with a threshold value and a spectrum matching method, calibrating the threshold value according to the magnetic field characteristics of the existing underwater vehicle, adopting short-time Fourier transform signal spectrum, comparing the threshold value with known submarine characteristic spectrum data, and prompting if the similarity exceeds a set threshold value. According to the detection method, the measurement precision and the anti-interference capability can be improved, and the method is suitable for real-time monitoring of weak magnetic anomalies (such as magnetic moment disturbance of an underwater vehicle).

The invention provides a target submarine path prediction and tracking method for an unmanned ship, and belongs to the technical field of unmanned ship dynamic tracking. Track data are collected in various sea areas through a sonar radar array sensor of the underwater unmanned ship, and the comprehensiveness and robustness of the data are ensured. The core of the method is that a multi-head attention mechanism and a target submarine trajectory prediction model of an LSTM network are combined, trajectory features can be accurately captured, the moving trajectory of a future target submarine can be predicted, particularly, an environment sensing module is introduced, the influence of obstacles around the target submarine on target submarine trajectory prediction is considered, and the target submarine trajectory prediction accuracy is improved. And the prediction accuracy is improved. In the training process, a model interaction strategy is adopted to optimize the model performance and robustness. Finally, the system is successfully deployed in the unmanned ship, collects data in real time, predicts a target trajectory, guides the unmanned ship to accurately track, and provides powerful technical support for the fields of ocean exploration, resource development, safety maintenance and the like.

The invention discloses a multi-beam backscattering intensity jump correction method, which takes a multi-beam measurement strip as a unit, automatically detects backscattering intensity jump generated by factors such as equipment parameter setting through a Gaussian weighting function, and selects a moving window to perform difference compensation by using a weighted average value. And carrying out iterative detection on the repaired intensity data and repairing the jump point until the jump point converges to 0. An example calculation result shows that the method can effectively detect and repair the intensity jump in the multi-beam strip, improve the processing efficiency and quality of the backscattering intensity data of the multi-beam strip, and improve the analysis accuracy of the submarine landform of the multi-beam intensity data.

The invention belongs to the technical field related to tunnels, and provides a subsea tunnel cross-fault water inrush catastrophe early warning decision-making method and system in order to solve the problems of inaccurate water inrush recognition, lack of interpretability and the like when an existing subsea tunnel passes through a fault zone high-risk scene. Full-process response control from weighting, prediction to explanation of the input features is realized; driving force analysis is carried out by adopting an interpretable model, so that a transparent and credible risk assessment result is provided; and by combining key driving force in the multi-source heterogeneous data and through numerical simulation of the water inrush catastrophe condition, real-time identification and early warning of the tunnel water inrush risk are comprehensively realized, the identification accuracy of the water inrush risk in the tunnel construction process and the completeness of an early warning mechanism are effectively improved, and the method has important engineering application value.

The invention relates to the field of submarine structure detection, in particular to a submarine water intake structure hidden danger detection method based on acousto-optic joint detection. According to the method, through a multi-source data acquisition and intelligent fusion technology, including centimeter-level high-resolution sonar sounding, water body layer structure acoustic imaging, ROV optical camera shooting observation and laser calibration, scouring, crack and blockage information of the seabed grating is comprehensively obtained, and the seabed grating is comprehensively identified by adopting adaptive enhancement, threshold segmentation and spatial interpolation algorithms. The problems that a traditional sonar imaging blind area exists, the target boundary is fuzzy and the biological adhesion thickness is difficult to quantify are solved, and high-precision and multi-dimensional detection of seabed structure damage, blockage and scour forms is achieved. According to the overall scheme, the detection integrity and accuracy are improved, the submarine environment safety monitoring capacity is enhanced, and reliable technical support is provided for operation and maintenance of submarine facilities.

The invention discloses a submarine topography super-resolution reconstruction method based on window displacement multi-source fusion, and aims to solve the problem of precision attenuation caused by absence of multi-beam truth value evaluation and resolution improvement of an existing neural network submarine topography reconstruction method. The method comprises the following steps of: obtaining gravity anomaly, gravity vertical gradient, vertical line deviation component, submarine topography background and ship survey water depth multi-source data of a target sea area; constructing a residual U-Net attention neural network model, and performing training by taking multi-source data extracted by a 11 * 11 window and position codes as input; moving the trained model sampling window in a staggered manner according to a target resolution step length; extracting data points in the window during movement and injecting position codes; and outputting a high-resolution water depth predicted value based on the position code and the window data. The reconstruction precision is improved by fusing physical quantities, the multi-resolution robustness is guaranteed by a window displacement mechanism, and the medium-frequency feature reconstruction capability is enhanced by a residual U-Net attention model.

The invention relates to a large-scale offshore engineering geologic model modeling system and method, and relates to the technical field of offshore engineering geologic investigation and modeling. According to the method, through the steps of multi-source data acquisition, preprocessing, fusion, three-dimensional geological modeling, model optimization, dynamic updating, visual analysis and the like, large-scale geological survey data can be efficiently processed, a high-precision three-dimensional geological model is generated, and dynamic updating and visual analysis are supported. The method has the advantages of high efficiency, high precision, real-time performance, engineering applicability and the like, and is suitable for geological modeling and geological condition analysis of engineering such as offshore wind power, submarine pipelines, ocean platforms and the like.

The invention discloses a submarine searching sonar buoy array position optimization method based on a non-dominated sorting genetic algorithm NSGA-III, and the method comprises the steps: introducing a time scale factor in combination with the initial and maneuvering positions of a submarine, and obtaining a position probability distribution function of the submarine after maneuvering; a buoy position is generated in the whole search area according to probability distribution, more initial array position individuals are generated near a high-probability area, and the exploration tendency of a population to a key area is improved; when reference lines are selected during non-dominated sorting, fusion density estimation is added, so that the reference lines at individual sparse positions are denser; when the Pareto front is selected to be reserved, a reduced-proportion front-edge reservation method is selected, and except for the first front edge, subsequent individual reservation is gradually reduced in a reduced-proportion mode until the population scale is reached; introducing a gene adaptation entropy crossover threshold in the crossover part, adopting a priority retention strategy for the parent with high fitness, and then performing crossover operation on the remaining part; and the potential sonar buoy array position optimization is realized.

The invention provides an artificial intelligence submarine topography inversion system and method using gravitational field spatial spectrum data, and the system comprises a gravitational field spatial spectrum calculation module which uses a plurality of band-pass filters to intercept gravity data under different wavelengths; and the gravity-water depth mapping relation establishing module is used for processing gravity and water depth data and establishing a correlation between the gravity and water depth data. A gravitational field spatial spectrum of a sparse ship water depth measuring position is obtained and is paired with water depth data. Dividing the data set into a training set and a test set in proportion; and designing an artificial intelligence model suitable for a regression task for training and predicting the water depth. And the artificial intelligence submarine topography inversion module is used for predicting a water depth value by using the gravitational field spatial spectrum of the trained model input test set, and evaluating a prediction effect through a precision index. The method has the advantages that the characteristics of the gravity data are enriched through the calculation of the gravity field spatial spectrum, and different degrees of influences of gravity on terrain inversion are considered.

The invention provides a calculation method for propagation of underwater explosion shock waves in a non-uniform acoustic flow field, and the method comprises the steps: simulating the propagation of the underwater explosion shock waves in a non-uniform fluid through an axial symmetry calculation model of an underwater explosion load in the non-uniform fluid based on a local discontinuous Galerkin method and a continuity condition; according to the method, a calculation model special for heterogeneous fluid is constructed, and continuous conditions are combined, so that the propagation process of underwater explosion shock waves in a heterogeneous flow field containing a sound velocity discontinuous interface and a sound velocity gradient is effectively simulated. According to the method, the influence of the sound velocity spring layer interface on the underwater explosion shock wave propagation path and the load peak value can be accurately analyzed, and more reliable underwater explosion load data are provided for the action of the submarine near the sound velocity spring layer. According to the invention, the influence of the flow field sound velocity gradient on the underwater explosion load and cavitation characteristics can be effectively studied, and the design and construction scheme of the protection ship and maritime work structure is optimized according to more accurate underwater explosion load input data.

The invention relates to a seabed sand wave and pipeline interaction numerical simulation method and system and a readable medium. The method comprises the following steps: selecting a sub-model under an environment dynamic simulation model according to environment data; selecting a sub-model under the sediment transportation simulation model according to the seabed sediment data; whether a fatigue stability simulation model needs to be carried out is selected according to the pipeline type, if the pipeline is a rigid pipeline, the fatigue stability simulation model is not started, and otherwise, the fatigue stability simulation model is started; starting a sub-model of the protection and treatment simulation model; determining a computational domain of a numerical simulation model, adjusting grid boundary conditions through an environment dynamic simulation model, and combining all selected models to form a final numerical simulation model; and inputting to-be-tested material parameters and environmental parameters into the final numerical simulation model to obtain a seabed sand wave and pipeline interaction numerical simulation result. According to the method, a numerical simulation result which better conforms to the dynamic change process of the sand waves in a real environment can be obtained, and the dynamic change of the seabed sand waves can be better understood and predicted.

The invention discloses a data center design and construction method for connecting a steel cylinder and a submarine pipe gallery, and belongs to the technical field of submarine data center construction. The steel cylinder and the submarine pipe gallery are connected through a special connecting structure, and meanwhile, a design method and a construction method for connecting the steel cylinder connected with the sea surface and the submarine pipe gallery are provided; the data center built by the method can transfer personnel and materials on the sea surface and the seabed through connection of the steel cylinder and the seabed pipe gallery, and the problem that connection and transfer of the seabed data center and shore-based resources are difficult is solved.

The invention discloses a multifunctional underwater vehicle. The multifunctional underwater vehicle comprises a ship body, a propeller, a rotating driver and a control device, a ship sealing cavity is formed in the ship body, a driving opening is formed in the outer side wall of the ship body, and the ship sealing cavity communicates with the driving opening; the driving openings are formed in the left side and the right side of the ship body in the advancing direction, and the driving openings in each side are arranged in pairs and distributed on the same straight line according to the front-back relation. The rotating drivers are arranged in the ship sealing cavity, and each driving opening corresponds to one rotating driver; the output end of each rotating driver horizontally extends out of the driving opening, is connected to the propeller and is used for driving the propeller to rotate by any angle; the control device is in communication connection with the rotating driver and the propeller. According to the scheme, one or more propellers are independently adjusted according to needs during underwater navigation of the underwater vehicle, so that rotation, constant-speed driving, accelerated driving, deep diving and floating are achieved during underwater navigation, and the problem that the underwater navigation function is insufficient due to the fact that the propellers of an existing underwater vehicle are single in function is solved.