Submarine cable burial depth determination method and system

Abstract

The invention provides a submarine cable burial depth determination method and system, and relates to the technical field of submarine cable laying. The method comprises the following steps: dividing grid units on a target sea area according to an initial route of a submarine cable, and collecting marine environment data, ship AIS data, anchorage device data and other human activity data of the target sea area; constructing a multi-time-scale ship density distribution diagram based on the ship AIS data; establishing a finite element simulation model of a coupling anchor body-anchor chain system based on the marine environment data and the anchorage device data, and calculating the maximum penetration depth of each grid unit by using the finite element simulation model; and generating a burial depth safety margin of each grid unit along the initial route of the submarine cable according to the multi-time-scale ship density distribution diagram, and calculating a recommended burial depth value in combination with the maximum penetration depth. According to the invention, omnibearing and three-dimensional cognition of the surrounding environment of the cable route is realized, and the dynamic burial depth of the route can be accurately determined.

Description

A method and system for determining the burial depth of submarine cables Technical Field

[0001] This invention relates to the field of submarine cable laying technology, specifically to a method and system for determining the burial depth of submarine cables. Background Technology

[0002] As the core carrier of marine power transmission, the operational safety of submarine cables directly affects the stability of power supply. To protect the cables from external damage, they need to be buried at a certain depth. If the burial depth is too shallow, the cables are susceptible to damage from factors such as ship anchoring, marine organism attachment, and wave erosion. If the burial depth is too deep, it means a significant increase in construction time, ship fuel consumption, and equipment wear and tear, which will greatly increase construction costs and difficulty, and may also lead to mechanical damage during the cable laying process due to complex seabed geological conditions.

[0003] Burial depth is a key parameter determining the safety of submarine cables, but the design of burial depth is a complex systems engineering project. Existing methods for determining the burial depth of submarine cables are mostly based on static scenario design, usually only considering a single marine environmental factor or a fixed intensity of human activities. Moreover, the burial depth is mostly a fixed value, which cannot reflect the real-time changes in the marine environment and human activities. Fixed burial depth values ​​may result in huge waste of engineering costs in non-channel deep water areas, and may not even be sufficient to prevent penetration by extra-large anchors. Furthermore, they cannot cope with the increasing tonnage of ships and new types of anchors, making it difficult to achieve the optimal burial depth planning that balances safety and cost. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and system for determining the burial depth of submarine cables, so as to solve the problems of single data dimension and lack of dynamism in determining the burial depth of submarine cables.

[0005] To achieve the above objectives, the present invention employs the following technical solution: a method for determining the burial depth of a submarine cable, the method comprising: dividing a target sea area into grid cells according to the initial route of the submarine cable, and collecting multi-source data of the target sea area, the multi-source data including at least: marine environmental data, ship AIS data, anchor data, and other human activity data; constructing a multi-timescale ship density distribution map based on the ship AIS data, the timescale including at least annual, quarterly, or event-driven; establishing a finite element simulation model of a coupled anchor body-anchor chain system based on the marine environmental data and the anchor data, and calculating the maximum penetration depth of each grid cell using the finite element simulation model; generating a burial depth safety margin for each grid cell along the initial route of the submarine cable according to the multi-timescale ship density distribution map, and calculating a recommended burial depth value in conjunction with the maximum penetration depth.

[0006] A further improvement of the present invention is that, preferably, the construction of a multi-time-scale ship density distribution map based on the ship AIS data includes: classifying and marking ship activities in all grid cells according to the ship AIS data to obtain no-anchorage zones and non-no-anchorage zones; calculating the ship dynamic density in the spatiotemporal dimension of each grid cell in the non-no-anchorage zone; and generating a multi-time-scale ship density distribution map based on the ship dynamic density in the spatiotemporal dimension of each grid cell.

[0007] Preferably, the non-restricted anchorage zone includes an anchorage area and a navigation area. The calculation of the ship dynamic density in the spatiotemporal dimension for each grid cell of the non-restricted anchorage zone includes: for each grid cell of the anchorage area, calculating the ship dynamic density according to a first formula, where the first formula is: For each grid cell in the navigation area, the ship dynamic density is calculated according to the second formula, which is: Among them, the first weight coefficient is the ship type weight, the second weight coefficient is the anchoring risk weight, and the third weight coefficient is the towing risk weight.

[0008] Preferably, the finite element simulation model includes: a drop anchor simulation model and a towed anchor simulation model; the step of establishing a finite element simulation model of the coupled anchor body-anchor chain system based on the marine environment data and the anchor data includes: obtaining the basic parameters required for modeling based on the marine environment data and the anchor data; establishing the drop anchor simulation model and the towed anchor simulation model in the finite element simulation environment using a fluid-structure interaction method based on the basic parameters, wherein the fluid-structure interaction method refers to establishing a computational fluid dynamics model that includes the anchor body, anchor chain, and seabed soil and a model simulating the fluid domain around the anchor body, and performing bidirectional data exchange; and calibrating and verifying the drop anchor simulation model and the towed anchor simulation model through physical experiments and field measurements.

[0009] Preferably, in the fluid-structure interaction method, the seabed soil model adopts a generalized plastic constitutive model that can reflect the soil strain rate effect and cyclic loading strength degradation.

[0010] Preferably, the step of calculating the maximum penetration depth of each grid cell using the finite element simulation model includes: extracting a representative ship for each grid cell based on the ship density distribution map, and extracting matching anchor parameters from the anchor data based on the representative ship, wherein the representative ship refers to the ship type with the largest tonnage appearing in each grid cell; obtaining the seabed geological parameters of each grid cell based on the marine environmental data; inputting the anchor parameters and seabed geological parameters of each grid cell into the anchor dropping simulation model and the anchor dragging simulation model respectively to obtain the anchor dropping impact depth and the anchor dragging plowing depth; and taking the larger of the anchor dropping impact depth and the anchor dragging plowing depth as the maximum penetration depth of the current grid cell.

[0011] Preferably, the recommended burial depth value is the sum of the burial depth safety margin and the maximum penetration depth; the step of generating the burial depth safety margin for each grid cell along the initial route of the submarine cable based on the multi-timescale ship density distribution map includes: determining the basic margin value for each grid cell based on the multi-timescale ship density distribution map; extracting the representative ships and their occurrence frequencies for each grid cell based on the ship density distribution map, and determining the margin variation coefficient for each grid cell based on the occurrence frequency of the representative ships; and calculating the burial depth safety margin based on the basic margin value and the margin variation coefficient for each grid cell.

[0012] Preferably, the multi-timescale ship density distribution map includes at least annual comprehensive layer, quarterly layer, and event-driven layer ship density distribution maps; determining the margin base value of each grid cell based on the multi-timescale ship density distribution map includes: determining the initial margin value of each grid cell based on the annual comprehensive layer ship density distribution map; extracting seasonal fluctuation grid cells based on the quarterly layer ship density distribution map and determining the first margin fluctuation value of the seasonal fluctuation grid cells; extracting emergency fluctuation grid cells based on the event-driven layer ship density distribution map and determining the second margin fluctuation value of the emergency fluctuation grid cells; and calculating the margin base value of each grid cell based on the initial margin value, the first margin fluctuation value, and the second margin fluctuation value.

[0013] Preferably, the method further includes: correcting the recommended burial depth value by combining geological feasibility, other human activity data, and equipment capabilities, and outputting the final burial depth value.

[0014] A system for determining the burial depth of a submarine cable includes: a data collection module for dividing a target sea area into grid cells based on the initial route of the submarine cable and collecting multi-source data of the target sea area, including at least marine environmental data, ship AIS data, anchor data, and other human activity data; a first analysis module for constructing a multi-timescale ship density distribution map based on the ship AIS data, wherein the timescale includes at least annual, quarterly, or event-driven data; a second analysis module for establishing a finite element simulation model of a coupled anchor body-anchor chain system based on the marine environmental data and the anchor data, and calculating the maximum penetration depth of each grid cell using the finite element simulation model; and a burial depth calculation module for generating a burial depth safety margin for each grid cell along the initial route of the submarine cable based on the multi-timescale ship density distribution map, and calculating a recommended burial depth value in conjunction with the maximum penetration depth.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a method and system for determining the burial depth of submarine cables. In the above-mentioned method for determining the burial depth of submarine cables, burial depth analysis is performed by collecting multi-source data. This approach has established a comprehensive and multi-dimensional understanding of the surrounding environment of cable routes, encompassing "sea (geology and hydrology), air (ship activity), and time (planning activities)," thus preventing misjudgments caused by missing or incomplete data. By constructing multi-timescale ship density distribution maps, it is possible to accurately capture the drastic fluctuations in ship activity during seasonal fishing seasons, typhoon sheltering, and other special events. Customized risk assessments can be implemented for specific high-risk periods such as peak fishing seasons and typhoon sheltering, significantly improving the real-time nature and accuracy of risk assessments. Furthermore, by establishing a coupled finite element simulation model of the anchor body and anchor chain, particularly incorporating fluid-structure interaction and an advanced soil constitutive model considering strain rate and pore pressure effects, and verifying and correcting it through physical experiments and data assimilation algorithms, the model can more realistically simulate the complex physical processes of the interaction between the anchor and the seabed. This allows the predicted maximum penetration depth to more closely approximate reality, providing a reliable theoretical basis for burial depth design. Based on a dynamic burial depth safety margin, differentiated designs are implemented for deep burial in high-risk areas and shallow burial in low-risk areas. While ensuring safety, this avoids excessive investment in low-risk areas, significantly optimizing the project's economic efficiency. Attached Figure Description

[0016] Figure 1 is a flowchart illustrating a method for determining the burial depth of a submarine cable provided by the present invention; Figure 2 is a flowchart illustrating a method for constructing a multi-timescale ship density distribution map provided by the present invention; Figure 3 is a flowchart illustrating a method for generating the burial depth safety margin for each grid cell provided by the present invention; Figure 4 is a structural schematic diagram illustrating a system for determining the burial depth of a submarine cable provided by the present invention. Detailed Implementation

[0017] Hereinafter, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," "third," or "fourth" may explicitly or implicitly include one or more of that feature.

[0018] The synchronization method provided in this application can be applied to mobile phones, tablets, wearable devices, in-vehicle devices, augmented reality (AR) / virtual reality (VR) devices, laptops, and ultra-mobile personal computers. In this application, the specific type of terminal device is not limited to terminal devices such as mobile personal computers (UMPCs), netbooks, and personal digital assistants (PDAs).

[0019] It should be noted that the terms "first," "second," etc., used in the specification and drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0020] Figure 1 is a flowchart illustrating a method for determining the burial depth of a submarine cable provided by the present invention. Referring to Figure 1, the method includes: S11, dividing the target sea area into grid cells according to the initial route of the submarine cable, and collecting multi-source data of the target sea area. The multi-source data includes at least: marine environmental data, ship AIS data, anchor data, and other human activity data.

[0021] Specifically, it is understandable that there are many factors affecting the burial depth of submarine cables, such as seabed topography, the distribution density of ships in the sea area, the equipment to be buried, etc. The seabed topography and the ships passing through the sea area are different in different sea areas, so it is necessary to collect multi-source data of the target sea area first.

[0022] The initial route of a submarine cable refers to the predetermined path along which the cable is laid on the seabed in the target sea area. This route can be determined in advance using integrated marine geological and geophysical survey techniques, and the initial route of the submarine cable will vary depending on the sea area.

[0023] The target sea area refers to the sea area where submarine cables need to be laid, such as the Jiangsu sea area. This area has numerous ports along its coast, including Lianyungang, Dafeng, and Lüsi, as well as dense shipping channels, large fishing areas, and offshore wind farms. The diverse types of vessels, from large cargo ships to small fishing boats, create complex risk sources. Furthermore, most of the Jiangsu sea area is an accumulation-type shallow continental shelf with a very gentle seabed slope and complex seabed composition. Nearshore seabed is dominated by silty mud and muddy silt, resulting in a high probability of anchoring and dragging incidents. Compared to nearshore seabed, the deeper sea gradually transitions to fine sand and medium sand, and the seabed may harden. While the risk of anchor damage is relatively low, the initial potential energy required for anchoring is greater, and the construction difficulty and cost are higher.

[0024] The method of dividing the target sea area into grid cells based on the initial route of the submarine cable includes: on the electronic nautical chart of the target sea area, taking 5km on each side of the initial route of the submarine cable as the analysis area, and dividing the analysis area into "grid cells". The grid size can be set to 100m×100m, or it can be set to other sizes according to actual needs. This invention does not limit this.

[0025] The marine environmental data includes at least seabed geological data, hydrological data, and geomorphological data. Seabed geological data refers to geological types, such as silt, clay, sand, gravel, rock, and mixed soil. Hydrological data includes water depth, currents, waves, water temperature, and salinity. Geomorphological data refers to seabed slope or obstacles. There are many ways to acquire marine environmental data, such as using multibeam echo sounders to create accurate seabed maps, using side-scan sonar to identify obstacles such as reefs, shipwrecks, sand dunes, and gullies, and using shallow seismic profilers to analyze the geological structure several meters to tens of meters below the seabed to determine the type and stratification of the seabed, specifically the types of seabed such as sand, mud, clay, and rock.

[0026] The ship AIS (Alarm Indication Signal) data refers to static information, dynamic information, and voyage information related to the ship. Generally, it is necessary to obtain ship AIS data in the sea area 5km on both sides of the initial route of the submarine cable to ensure that the ship AIS data can fully cover the initial route of the submarine cable.

[0027] The ship's AIS data includes at least the ship's identity information, type, draft, speed, heading, location information, and ship status. Ship identity information refers to the ship's unique identifier, such as the MMSI code, which is generally embedded in the ship's AIS equipment and can be decoded by the AIS receiver. Ship type includes cargo ships, oil tankers, engineering vessels, etc., and standard codes are predefined in the AIS protocol, such as 70 for cargo ships, 80 for oil tankers, 90 for engineering vessels and other vessels, and 30 for fishing vessels. Ship draft refers to the depth of the ship below the waterline when navigating or anchoring in the target sea area, mainly reflecting the ship's cargo capacity; a deeper draft usually indicates a larger load. This is automatically input by the ship's onboard draft sensor connected to the AIS equipment or manually input by the crew. Real-time speed refers to the ship's actual speed relative to the ground in the target sea area, and heading refers to the direction the ship's bow is pointing. This is generally provided by the ship's GPS positioning system and navigation equipment such as gyrocompasses and is automatically integrated into the AIS signal. Latitude and longitude coordinates refer to the actual position of a ship, determined by its GPS positioning system. Ship status refers to the ship's current condition, generally categorized as anchored, at anchor, or underway.

[0028] The anchorage data includes anchorage type, weight, anchor chain parameters, and material mechanical properties. Anchorage types include Hall anchors, Spek anchors, and high-holding-power anchors; anchorage weights generally range from 500kg to 20000kg; anchor chain parameters include at least the number of chain links and the length of each link, anchor body geometry parameters, etc., with the chain diameter ranging from 22mm to 120mm. Anchor body geometry parameters refer to the length of the lugs and the width of the cap, etc.; material mechanical properties refer to attributes such as the anchorage's yield strength and modulus of elasticity. This anchorage data is collected through ship surveys and anchorage manufacturer databases.

[0029] Other human activity data includes data on submarine engineering activities, which may be projects currently under construction or projects that have been planned and are temporarily implemented, such as the location and timing of nearby submarine pipeline laying and offshore oil and gas platform construction.

[0030] S12, construct a multi-timescale ship density distribution map based on the ship AIS data, wherein the timescale includes at least annual, quarterly or event-driven.

[0031] Specifically, it's understandable that submarine cables suffer from issues of over-protection or insufficient protection due to their burial depth, while marine activities exhibit strong spatiotemporal regularities. For example, seasonal variations exist: specific fishing grounds see a large influx of fishing vessels during the fishing season (e.g., spring and autumn), while almost none are present during the closed season; some marine engineering projects can only be carried out in the summer when sea conditions are favorable, leading to a high density of construction vessels during this period. Another example is diurnal variation: many cargo ships operate day and night to save costs or meet deadlines, but fishing boats and smaller vessels are typically more active during the day. Furthermore, for certain special events, such as typhoons, a large number of ships flock to sheltered anchorages before a typhoon arrives, transforming areas that might normally have low risk levels into extremely high-risk zones in a short period. Given these circumstances, simply using static vessel density distribution maps cannot capture these dynamic changes.

[0032] Specifically, it can also be understood that constructing a multi-timescale ship density distribution map based on the ship AIS data includes: classifying and marking ship activities in all grid cells according to the ship AIS data to obtain no-anchorage zones and non-no-anchorage zones; calculating the ship dynamic density in the spatiotemporal dimension of each grid cell in the non-no-anchorage zone; and generating a multi-timescale ship density distribution map based on the ship dynamic density in the spatiotemporal dimension of each grid cell.

[0033] S13. Based on the marine environment data and the anchor data, establish a finite element simulation model of the coupled anchor body-anchor chain system, and use the finite element simulation model to calculate the maximum penetration depth of each grid cell.

[0034] Specifically, it is understandable that traditional simulation models rely heavily on empirical formulas based on limited experimental data, failing to reflect complex interactions. This invention utilizes finite element software to simulate the marine environment and the processes of anchoring and towing. It fully considers various factors such as the forces between the anchor body and the anchor chain, the resistance of water to the anchor chain, and the impact of multiple anchor impacts on the seabed. It can clearly distinguish between two distinct damage modes: anchoring impact (instantaneous, deep pit) and towing scraping (long distance, trench). It also calculates the maximum depth of impact for each mode, achieving high-precision simulation of anchoring and towing in the target sea area.

[0035] Because the weight of the anchor chain and fluid resistance significantly affect the anchor's descent speed and attitude during anchoring, and the shape, weight, and friction with the seabed directly determine the magnitude and direction of the towing force transmitted to the anchor during towing, traditional methods generally simplify the anchoring process as a mass block with initial kinetic energy impacting the seabed, completely ignoring the crucial role of the anchor chain. This invention, however, couples a finite element simulation model of the anchor-anchor chain system, simulating the dynamic, interactive mechanical behavior between the anchor and chain, forming a complete force chain. This ensures the complete and realistic force flow transmission path from the ship to the anchor, resulting in a more accurate penetration depth.

[0036] The finite element simulation model includes an anchor dropping simulation model and a towing anchor simulation model. The anchor dropping simulation model is configured to simulate the process of the anchor impacting and penetrating the seabed with a vertical initial velocity to calculate the anchor dropping impact depth. The towing anchor simulation model is configured to simulate the seabed scraping process of the anchor under the action of horizontal towing force at the pre-penetration initial depth to calculate the towing anchor scraping depth.

[0037] The establishment of a finite element simulation model of the coupled anchor body-anchor chain system based on the marine environment data and the anchor data includes: S131, obtaining the basic parameters required for modeling based on the marine environment data and the anchor data.

[0038] The marine environmental data includes at least seabed geological data, hydrological data, and geomorphological data, while the anchor data includes anchor type, weight, anchor chain parameters, and material mechanical properties. The basic parameters required for modeling include anchor geometry, material parameters, anchor chain parameters, and seabed geological parameters, all of which can be directly obtained from the marine environmental data and anchor data.

[0039] S132, Based on the aforementioned basic parameters, establish a drop anchor simulation model and a drag anchor simulation model respectively in the finite element simulation environment using a fluid-structure interaction method.

[0040] The fluid-structure interaction method refers to establishing a computational fluid dynamics model that includes the anchor body, anchor chain, and seabed soil, and simulating the fluid domain around the anchor body, and then exchanging data bidirectionally.

[0041] In the fluid-structure interaction method, the anchor body model requires mesh refinement for key components such as the anchor claws and anchor crown. The anchor chain model is modeled using hinged flexible multibody dynamic beam elements to accurately simulate its large deformation and bending behavior.

[0042] In the fluid-structure interaction method, the seabed soil model is a layered model, generally employing a generalized plastic constitutive model that reflects the soil strain rate effect and cyclic loading strength degradation. In other embodiments, the seabed soil model uses a boundary surface model that reflects the soil strain rate effect and cyclic loading strength degradation; this invention does not limit this approach. For saturated soft clay substrates, it is necessary to activate coupled pore pressure-stress analysis to simulate the excess pore water pressure caused by anchor impact or towing and its dissipation process.

[0043] Specifically, establishing the anchoring simulation model using fluid-structure interaction includes: step a1, creating geometric models of the fluid domain and structural domain; further, creating precise three-dimensional geometric models of the anchor body and anchor chain as the structural domain; establishing a geometric model of a sufficiently large water body region around the anchor body, i.e., establishing a computational fluid dynamics model simulating the fluid domain around the anchor body; and determining the anchor body surface and anchor chain surface as the fluid-structure interaction interface.

[0044] Step a2: Set the physical properties and mesh generation for the fluid and structural domains. Further, define the physical properties of the fluid domain, such as seawater density and viscosity, and select a transient CFD solver based on the Navier-Stokes equations as the fluid solver. Mesh the fluid domain, refining the mesh in areas near the anchor surface to accurately capture the boundary layer and complex flow phenomena. Define the physical properties of the structural domain, such as the anchor steel's density, elastic modulus, Poisson's ratio, and other material properties, and select a transient dynamics analysis solver as the structural solver. Perform solid mesh generation on the anchor body. Similarly, refine the mesh appropriately in areas where severe deformation may occur.

[0045] Step a3: Define the fluid-structure interaction interface and data exchange mechanism; further, designate the anchor surface as the fluid-structure interaction interface; the data exchange mechanism includes: the fluid pressure and shear stress acting on the anchor surface calculated by the fluid solver are transmitted as loads to the structural solver; and the displacement and velocity of the anchor calculated by the structural solver are fed back to the fluid solver for dynamically updating the boundary of the fluid domain.

[0046] Step a4: Set the boundary and initial conditions for the anchoring process. Further, set the initial flow field of the fluid domain to a still water body, and the far-field boundary is typically set as a pressure outlet or a free-sliding wall. The initial conditions for the structural domain are: place the anchor body in an initial position above the fluid domain and assign it an initial vertically downward velocity; apply gravitational acceleration; the fluid force will be automatically transferred through the coupling interface without manual application. The anchor chain is constrained so that the top of the anchor chain can be set to free or subject to a certain tension condition.

[0047] Step a5: Perform transient co-solution to obtain the velocity and acceleration time history curves during the anchor's descent, as well as possible attitude changes such as pitch and yaw. After the anchor contacts the seabed soil model and stops moving, read its final vertical displacement, which is the anchor penetration depth after considering hydrodynamic effects.

[0048] Specifically, establishing a towed anchor simulation model using fluid-structure interaction includes: step b1, creating geometric models of the fluid domain and structural domain; further, creating precise three-dimensional geometric models of the anchor body and anchor chain; establishing a water model in the anchor body, seabed surface, and above, with the fluid domain covering the expected towing path of the anchor. The interface between the anchor body surface, potentially exposed anchor chain portions, and the fluid domain is defined as the fluid-structure interaction interface; simultaneously, the contact interface between the anchor body, anchor chain, and seabed soil is defined.

[0049] Step b2: Set the physical properties and mesh generation for the fluid domain and structural domain; further, define the physical properties of the fluid domain, such as the density and viscosity of seawater, and refine the mesh in the near-wall region; define the physical properties of the structural domain, such as steel properties. In the drag path region, the mesh must be very fine to capture the trench formation process.

[0050] Step b3 involves performing a crucial geostress equilibrium analysis; furthermore, the soil is subjected to its own weight to generate an initial stress field and deformation, simulating its original bearing state. Only in the equilibrium state can the soil response obtained by applying a drag force be considered realistic.

[0051] Step b4, define the interaction; further, define the bidirectional data exchange between the anchor body and part of the anchor chain and the surrounding water; define the contact relationship between the anchor-chain-soil, including: normal behavior, indicating that the contact surfaces cannot intrude into each other; tangential behavior, simulating the sliding friction between the anchor and the soil.

[0052] Step b5 sets the boundary conditions and loads for the towing process; further, the initial condition is to pre-embed the anchor at an initial depth in the seabed soil; the load condition is to apply a horizontal velocity or horizontal displacement at the top node of the anchor chain, with the force transmitted to the anchor body through the anchor chain, rather than being applied directly to the anchor body. Simultaneously, the vertical displacement of this top node is constrained to simulate the constraints of a surface vessel.

[0053] Step b6: Perform transient collaborative solution to obtain the change in tension required during the dragging process. Observe the time history curve of the vertical displacement of the anchor's center of gravity. This will determine the final stable depth at which the anchor will plow after adjusting from the initial depth. This stable depth is the dragging and plowing depth.

[0054] S133, The anchor dropping simulation model and the anchor dragging simulation model are corrected and verified through physical experiments and field measurements.

[0055] Specifically, experimental and measured data are first obtained through indoor physical experiments and outdoor field measurements. Then, the finite element simulation model is corrected based on the experimental data, and finally, the finite element simulation model is verified using the measured data.

[0056] Physical tests can be conducted by establishing test plans for both drop anchors and towed anchors. For example, for drop anchors, a large, deep test pool can be built with different bottom substrate modules. The pool can be equipped with an overhead crane, a release mechanism, a high-speed camera system, and a sensor array embedded in the soil to measure data such as the penetration depth, impact velocity, anchor attitude, and soil response after the anchor model is released from different heights. Alternatively, for towed anchors, a long, narrow trench can be built, filled with standard seabed soil samples, and equipped with a sophisticated linear traction system, multi-axial force sensors, and depth-measuring sensors. The anchor can be pre-embedded at a certain depth, and the traction system can drag it horizontally at a constant speed to measure data such as the scraping depth, dragging resistance, and trench morphology.

[0057] The on-site measurement was conducted near the initial route of the submarine cable in the target sea area, in a representative geological location. Detailed records were kept of the on-site testing process, including key operational parameters such as the tonnage of the anchoring vessel, anchor type, water depth, anchor chain length, and towing speed. After anchoring, an underwater robot equipped with a multibeam echo sounder or side-scan sonar was used to perform a fine scan of the anchor pit and towing trajectory, accurately measuring the actual penetration and scraping depth.

[0058] Furthermore, based on the parameters set by the physical test, such as the anchor, initial velocity / depth, and soil sample type, and the estimated soil parameters, the anchor drop simulation model and the anchor dragging simulation model are run, and the simulation results are compared with the test data of the physical test. The process is iterated until the error between the simulation results and the test data meets the convergence condition, thus completing the correction of the finite element simulation model.

[0059] After completing the calibration and parameter calibration of the finite element simulation model, the working condition parameters from the measured data and the geological parameters obtained from the survey are input into the finite element simulation model calibrated by the laboratory test data. If the error is ≤10%, the model is considered to have passed the final verification, has high confidence, and can be used for predictive design. Otherwise, physical tests need to be carried out on the finite element simulation model again.

[0060] Specifically, it can also be understood that the calculation of the maximum penetration depth of each grid cell using the finite element simulation model includes: S134, extracting the representative ship of each grid cell based on the ship density distribution map, and extracting the matching anchor parameters from the anchor data based on the representative ship to obtain the anchor parameters in each grid cell, wherein the representative ship refers to the ship type with the largest tonnage appearing in each grid cell.

[0061] Furthermore, gross tonnage is a key indicator for measuring ship size and anchor specifications; therefore, the ship with the largest tonnage among those appearing in each grid cell can be selected as the representative ship. In addition, this invention can pre-store the acquired anchor data in a database and configure the mapping relationship between different types of ships and standard anchors during storage. Thus, after determining the representative ship, the corresponding anchor parameters can be automatically matched and extracted.

[0062] S135, Obtain the seabed geological parameters for each grid cell based on the marine environmental data.

[0063] Furthermore, to ensure the high accuracy of the finite element simulation model, marine environmental data can be spatially matched with each grid cell to obtain accurate seabed geological parameters for each grid cell, such as soil type and its corresponding soil mechanical parameters. Soil mechanical parameters are usually determined through indoor geotechnical tests.

[0064] S136, input the anchor parameters and seabed geological parameters of each grid cell into the anchor dropping simulation model and the dragging anchor simulation model respectively to obtain the anchor dropping impact depth and dragging anchor scraping depth.

[0065] Furthermore, by calling the anchor drop simulation model and setting the scenario of the anchor drop simulation model according to the parameters of each grid cell, the anchor drop impact depth can be calculated; by calling the dragging anchor simulation model and setting the scenario of the dragging anchor simulation model according to the parameters of each grid cell, the dragging anchor scraping depth can be calculated.

[0066] S137, take the larger of the anchor impact depth and the dragging anchor scraping depth as the maximum penetration depth of the current grid cell.

[0067] Furthermore, the magnitudes of the anchor impact depth and the anchor scraping depth are determined. If the anchor impact depth is greater than the anchor scraping depth, the maximum penetration depth is the anchor impact depth; if the anchor impact depth is less than the anchor scraping depth, the maximum penetration depth is the anchor scraping depth.

[0068] S14. Based on the multi-timescale ship density distribution map, generate the burial depth safety margin for each grid cell along the initial route of the submarine cable, and calculate the recommended burial depth value in conjunction with the maximum penetration depth.

[0069] Specifically, it is understandable that after calculating the maximum penetration depth of different anchors in different marine environments during anchoring and towing using the finite element simulation model, the initial route of the submarine cable varies in different grid cells, and the types and numbers of ships passing through the sea area are different. High-density ship activity will also affect the penetration depth of the anchor. Moreover, ship density will also show different variation patterns at different time scales. Therefore, in order to lay the cable more safely, it is necessary to add a safety margin for burial depth as compensation based on the distribution of ship density.

[0070] Specifically, it can also be understood that the multi-timescale ship density distribution map includes at least annual comprehensive layer, quarterly layer, and event-driven layer ship density distribution maps; the step of generating the burial depth safety margin for each grid cell along the initial route of the submarine cable based on the multi-timescale ship density distribution map includes: determining the basic value of the margin for each grid cell based on the multi-timescale ship density distribution map; extracting representative ships and their occurrence frequencies for each grid cell based on the ship density distribution map, and determining the margin variation coefficient for each grid cell based on the occurrence frequency of the representative ships; calculating the burial depth safety margin based on the basic value of the margin and the margin variation coefficient for each grid cell, wherein the burial depth safety margin is the product of the basic value of the margin and the margin variation coefficient.

[0071] In some embodiments, after S14, the method further includes: S15, adjusting the recommended burial depth value based on geological feasibility, the other human activity data, and equipment capabilities, and outputting a final burial depth value.

[0072] The geological feasibility refers to whether the seabed topography supports cable laying; the other human activity data includes data on seabed engineering activities; the equipment capability refers to the equipment used for laying submarine cables. Commonly used laying equipment includes plow-type laying machines, hydraulic jet laying machines, and mechanical excavation laying machines. Plow-type laying machines are suitable for soft soil geology such as silt and sandy soil, hydraulic jet laying machines are suitable for geology such as sandy soil and clay, and mechanical excavation laying machines are suitable for geology such as hard soil layers and wind-blown rock layers.

[0073] Specifically, it is understood that when laying submarine cables, considerations must be given to whether there are obstacles, whether the equipment's processing capacity is exceeded, and whether there are conflicts with other submarine engineering projects. If necessary, the recommended burial depth value needs to be corrected. The process of correcting the recommended burial depth value and outputting the final burial depth value by combining geological feasibility, other human activity data, and equipment capabilities includes: Step c1, if the initial route of the submarine cable corresponding to any grid cell encounters an obstacle when laid according to the recommended burial depth value, the initial route of the submarine cable needs to be fine-tuned to bypass the obstacle, and the recommended burial depth value of the fine-tuned route needs to be recalculated. Alternatively, laying the cable according to the recommended burial depth value can be abandoned, and a surface protection method can be used instead. Surface protection methods include covering with rock mats or concrete protective covers.

[0074] Step c2: If the submarine cable corresponding to any grid cell is initially laid at the recommended burial depth value, and there is a conflict with other submarine engineering activity data, then the burial depth needs to be increased based on the recommended burial depth value, or the submarine cable can be laid directly using a pre-buried pipeline.

[0075] Step c3: If the recommended burial depth exceeds the equipment capacity when the submarine cable corresponding to any grid cell is initially laid according to the recommended burial depth, then other equipment needs to be used for laying. Alternatively, the recommended burial depth can be corrected based on the equipment capacity. For example, in some embodiments, correcting the recommended burial depth also includes: correcting the recommended burial depth in conjunction with cost risk. Specifically, correcting the recommended burial depth in conjunction with cost risk includes: Step d1: Calculating the corresponding ship time fee, equipment rental fee, fuel consumption, etc., as the project cost based on the recommended burial depth. Then, constructing a first curve of project cost versus burial depth with burial depth as the horizontal axis and project cost as the vertical axis. The first curve is an upward-accelerating curve. This is because the greater the burial depth, the lower the operating efficiency, the longer the time, and the project cost increases exponentially.

[0076] Step d2: Based on the dynamic ship distribution density of each grid cell, calculate the probability of cable damage, cable modification cost, and losses after cable failure as risk costs. Then, construct a second curve of risk cost versus burial depth with burial depth as the horizontal axis and risk cost as the vertical axis. The second curve is a downward-decreasing curve. In the initial stage of increasing burial depth, the risk cost drops sharply; however, when the burial depth exceeds a certain threshold, the risk decreases very slowly.

[0077] Step d3: Calculate the total cost curve based on the first and second curves. Since the total cost curve is usually a "U" or "L" shaped curve, take the lowest point on the total cost curve as the economically optimal burial depth.

[0078] The aforementioned method for determining the burial depth of submarine cables, through the collection of multi-source data for depth analysis, forms a comprehensive and three-dimensional understanding of the surrounding environment of the cable route, encompassing "sea (geology and hydrology), air (ship activity), and time (planned activities)," thus avoiding misjudgments caused by missing or incomplete data. By constructing multi-timescale ship density distribution maps, it is possible to accurately capture the drastic fluctuations in ship activity during special events such as seasonal fishing and typhoon sheltering. Customization can be carried out on demand for specific high-risk periods such as peak fishing seasons and typhoon sheltering, greatly improving the real-time performance and accuracy of risk assessment. By establishing a coupled anchor-anchor chain finite element simulation model, especially by introducing fluid-structure interaction and an advanced soil constitutive model considering strain rate and pore pressure effects, and verifying and correcting it through physical experiments and data assimilation algorithms, the model can more realistically simulate the complex physical processes of the interaction between the anchor and the seabed, making the predicted maximum penetration depth closer to the actual situation and providing a reliable theoretical basis for burial depth design. Based on dynamic burial depth safety margins, differentiated designs for deep burial in high-risk areas and shallow burial in low-risk areas are realized. While ensuring safety, excessive investment in low-risk areas was avoided, significantly optimizing the project's economic efficiency.

[0079] Figure 2 is a schematic flowchart of a method for constructing a multi-timescale ship density distribution map provided by the present invention. Referring to Figure 2, the method for constructing a multi-timescale ship density distribution map, that is, constructing a multi-timescale ship density distribution map based on the ship AIS data, includes: S22, classifying and marking ship activities in all grid cells according to the ship AIS data to obtain no-anchoring zones and non-no-anchoring zones.

[0080] The vessel AIS data includes at least the vessel's identity information, type, draft, speed, course, location information, and status. Vessel activity refers to the activities of vessels within each grid cell, including navigation, anchoring, and prohibited anchoring. Corresponding areas are divided into prohibited anchoring zones and non-prohibited anchoring zones, with the non-prohibited anchoring zone further divided into navigation zones and anchoring zones.

[0081] Specifically, firstly, based on the ship AIS data, all grid cells are classified and marked with ship activities to classify navigation areas and anchorage areas in each grid cell; then, according to preset anchorage prohibition regulations, grid cells that comply with the anchorage prohibition regulations are marked as anchorage prohibition areas. Preset anchorage prohibition regulations include marine protected areas, buffer zones directly above existing submarine pipelines, etc., thereby clarifying the characteristics of ship activities in different areas.

[0082] In some embodiments, since ships have continuous power during navigation, their speed is significantly greater than 0, and their position coordinates continuously change. Therefore, classifying and marking ship activities in all grid cells based on the ship's AIS data can be done by acquiring the ship's speed and heading from the AIS data, determining whether the ship's grid cell is in a navigation area or an anchorage area by identifying the speed, and if a ship's speed is found to be greater than a preset threshold, then the ship is underway and its grid cell is marked as a navigation area; if a ship's speed is found to be approximately zero, then the ship is underway and its grid cell is marked as a navigation area.

[0083] In other embodiments, ship activities are classified and marked in all grid cells based on the ship's AIS data. Alternatively, the ship's status in the AIS data can be obtained, and the grid cell in which the ship is located can be determined to be either a navigation area or an anchorage area by identifying the ship's status. If a ship's status is identified as anchored or at anchor, the grid cell in which the ship is located is determined to be an anchorage area; if a ship's status is identified as being at sea, the grid cell in which the ship is located is determined to be a navigation area.

[0084] S23, calculate the dynamic density of ships in the spatiotemporal dimensions of each grid cell in the non-no-anchorage zone.

[0085] Specifically, it is understandable that traditional submarine cable burial depth design mainly relies on static, long-term average nautical chart data and engineering experience, which cannot reflect the dramatic fluctuations in ship activity over time. In actual operations, different seasons see increased vessel density during peak fishing seasons; different daytime periods may present challenges, with certain cable sections experiencing high anchoring risks during the day due to fishing vessel operations, while at night, cargo ships dominate the traffic, leading to high anchoring risks; and during the 72-hour period of a typhoon, vessel density in the corresponding grid cells of the shelter area also surges. Therefore, to better analyze seasonal fishing activities, typhoon sheltering, and differences in daytime and nighttime navigation density, this invention introduces a multi-timescale analysis framework to deeply mine ship AIS data, generating a series of dynamic risk maps corresponding to different time dimensions.

[0086] Specifically, it can also be understood that in the spatiotemporal dimension, the time dimension uses year, quarter, month, week, day, hour, and event-driven time scales, while the spatial dimension uses grid cells as the spatial scale. When the time scale is annual or quarterly, the analysis corresponds to long-term average risk, which means that the average ship density within each grid cell needs to be calculated annually or quarterly, such as the average number of ships per week within a year. When the time scale is monthly, weekly, or daily, the analysis corresponds to average risk from a construction management perspective, which requires calculating the average ship density within each grid cell monthly, weekly, or daily. When the time scale is event-driven, the analysis corresponds to short-term extreme risks, such as the average number of ships per hour during a typhoon warning period of 72 hours.

[0087] In some embodiments, the non-restricted anchorage area includes anchorage areas and navigation areas. When a vessel is under navigation, it has continuous power, and the risk of laying submarine cables mainly comes from dragging anchors; while when anchored, the vessel lays its anchor and anchor chain, using the anchor's holding power and underwater friction to safely moor on the water surface, and the risk of laying submarine cables mainly comes from dropping anchor.

[0088] The calculation of the ship dynamic density in the spatiotemporal dimension of each grid cell in the non-restricted anchorage area specifically includes the following steps: S231, for each grid cell in the anchorage area, calculate the ship dynamic density according to the first formula, where the first formula is...

[0089] Among them, anchorage duration refers to the time that each vessel is in an anchored state within any grid cell; the first weight coefficient is the vessel type weight, the second weight coefficient is the anchoring risk weight, and the statistical duration is the statistical duration corresponding to each time scale.

[0090] S232, for each grid cell in the navigation area, calculate the ship dynamic density according to the second formula, which is:

[0091] Among them, the sailing time refers to the time that each ship is in a sailing state within any grid cell; the first weight coefficient is the ship type weight, the third weight coefficient is the anchoring risk weight, and the statistical time is the statistical time corresponding to each time scale.

[0092] In the above embodiments, the first weighting coefficient can be determined based on the type and tonnage of the vessel, such as 1.5 for engineering vessels, 1.2 for large cargo ships, and 1.0 for ordinary fishing vessels; the second and third weighting coefficients are set based on historical data or expert experience, generally 1.5; the third weighting coefficient is the anchoring risk weight, generally set to 0.85 based on historical data or expert experience. The total duration is the statistical duration corresponding to each time scale. For example, when the time scale is year, the total duration is one year; when the time scale is event-driven, the total duration is the duration of the event, such as the duration of a typhoon event.

[0093] S24 generates a multi-timescale ship density distribution map based on the ship dynamic density of each grid cell in the spatiotemporal dimension.

[0094] Specifically, it can be understood that on electronic nautical charts, the dynamic density of ships in each grid cell at different time scales is displayed in layers according to the time scale, resulting in multi-layered ship density distribution maps. For example, the annual comprehensive layer displays the average density distribution for the whole year through a single ship density distribution map, the quarterly layer displays the average density distribution for the four seasons of spring, summer, autumn, and winter through four ship density distribution maps respectively, and the event-driven layer displays the average density distribution during the duration of an event. The event-driven layer can include ship density distribution maps for multiple events, such as the ship density distribution map for Typhoon 1 during its duration and the ship density distribution map for Typhoon 2 during its duration.

[0095] Specifically, it can also be understood that the generation of multi-timescale ship density distribution maps based on the ship dynamic density of each grid cell in the spatiotemporal dimension includes: generating multi-layer ship density distribution maps according to time scales based on the ship dynamic density of each grid cell in the spatiotemporal dimension, wherein the multi-layer ship density distribution maps include at least annual comprehensive layer, quarterly layer and event-driven layer ship density distribution maps; for the ship density distribution map of the annual comprehensive layer, displaying the boundaries of anchorage area, navigation area and no-anchorage area, and visually rendering the calculated ship dynamic density of each grid cell using color gradient, that is, using different colors to represent different densities, such as blue for low density, yellow for medium density and red for high density.

[0096] In some embodiments, three density levels—low density, medium density, and high density—can be used to represent the ship density of each grid cell. In this case, the step of visualizing the calculated dynamic ship density of each grid cell using a color gradient includes: step e1, sorting the dynamic ship density of all grid cells from high to low to obtain a sorted density sequence; step e2, determining a density threshold from the sorted density sequence to classify the density levels, and dividing each grid cell into one of the three density levels—low density, medium density, and high density—based on the density threshold; for example, to classify the three density levels, two density thresholds are selected: a first density threshold and a second density threshold, wherein the first density threshold... A first density threshold is set at the 10th percentile for ship dynamic density, and a second density threshold is set at the 70th percentile for ship dynamic density. Grid cells with ship dynamic density greater than or equal to the first density threshold are defined as high-density cells, i.e., the top 10% of grid cells in terms of ship dynamic density. Grid cells with ship dynamic density greater than the second density threshold but less than the first density threshold are defined as medium-density cells, i.e., the 10% to 70% of grid cells in terms of ship dynamic density are defined as medium-density cells. Grid cells with ship dynamic density less than or equal to the second density threshold are defined as low-density cells, i.e., the bottom 70% of grid cells in terms of ship dynamic density are defined as medium-density cells. The first and second density thresholds can also be determined using other methods, which are not limited in this invention.

[0097] Step e3: Use different colors to render mesh cells of different density levels, such as using red to render high-density mesh cells, using yellow to render medium-density mesh cells, and using blue to render low-density mesh cells.

[0098] In other embodiments, the multi-timescale ship density distribution map also includes ship information passing through each grid cell, such as ship type, tonnage, frequency of occurrence, etc. A time slider can also be provided on the multi-timescale ship density distribution map, allowing users to view the ship density distribution at different times by dragging the slider.

[0099] In the aforementioned method for constructing multi-timescale vessel density distribution maps, by introducing vessel type weights and risk pattern weights, differentiated assessments are achieved for anchorage areas with anchoring risks and navigation areas with dragging risks. This provides precise and quantifiable input for subsequently determining the safety margin for burial depth. By introducing a multi-timescale analysis framework, multi-layered vessel density distribution maps are generated, including annual, quarterly, and event-driven maps. This overcomes the limitations of traditional reliance on static nautical chart data and can accurately capture the drastic fluctuations in vessel activity during seasons, day and night, and special events such as typhoons. This makes cable burial depth design no longer a compromise based on "annual average risk," but rather allows for on-demand customization for specific high-risk periods such as peak fishing seasons and typhoon sheltering, greatly improving the real-time performance and accuracy of risk assessment.

[0100] Figure 3 is a flowchart illustrating a method for generating a burial depth safety margin for each grid cell according to the present invention. Referring to Figure 3, the method for generating the burial depth safety margin for each grid cell, namely, generating the burial depth safety margin for each grid cell along the initial route of the submarine cable based on the multi-timescale ship density distribution map, includes: S31, determining the basic margin value for each grid cell based on the multi-timescale ship density distribution map.

[0101] Specifically, it can be understood that the ship density distribution of each grid cell is analyzed based on the number of ships passing through each grid cell corresponding to the initial route of the submarine cable. Higher density has a greater impact on burial depth. Therefore, different margin base values ​​can be set according to the actual density of each grid cell to achieve different burial depth safety margins for grids with different densities.

[0102] Specifically, it can also be understood that determining the basic value of the margin for each grid cell based on the multi-timescale ship density distribution map includes: S311, determining the initial value of the margin for each grid cell based on the ship density distribution map of the annual comprehensive layer.

[0103] Furthermore, based on the annual comprehensive layer's ship density distribution map analysis, the grid cells corresponding to high-density areas with a large number of ships in the target sea area throughout the year, such as grid cells covered by main waterways and permanent anchorages, are analyzed.

[0104] In some embodiments, determining the initial margin value for each grid cell based on the ship density distribution map of the annual comprehensive layer can be achieved by: determining the density level of each grid cell based on the ship density distribution map of the annual comprehensive layer, and determining the initial margin value for each grid cell based on the density level. Since a higher dynamic ship density within each grid cell represents a greater risk of ship density impacting burial depth, different initial margin values ​​can be set for grid cells of different density levels. That is, the number of initial margin values ​​is the same as the number of density levels. If the density levels are high density, medium density, and low density, then there are three initial margin values: a first initial margin value corresponding to the high density level, a second initial margin value corresponding to the medium density level, and a third initial margin value corresponding to the low density level. Generally, the first initial margin value is 1.0 meter, the second initial margin value is 0.5 meters, and the third initial margin value is 0.2 meters. The initial margin values ​​can also be adjusted to other values ​​according to actual operational needs; this invention does not limit this.

[0105] In other embodiments, determining the initial margin value for each grid cell based on the annual integrated layer's ship density distribution map can also be achieved by: determining the risk level of each grid cell based on a preset risk threshold and the multi-timescale ship density distribution map, and then determining the initial margin value for each grid cell based on the risk level. The number of preset risk thresholds is determined according to the number of risk levels. If it is necessary to divide into three risk levels, then two preset risk thresholds are required. The specific preset risk thresholds can be set based on experience. For example, a high-risk threshold is set when more than one ship of 300 gross tons or more anchors per day on average in the grid cell, and a medium-risk threshold is set when no more than seven ships appear per week on average in the grid cell. In this case, the risk level is determined by comparing the ship information in each grid cell with the preset risk-sharing threshold. Then, the initial margin value for each grid cell is determined based on the risk level, such as the fourth initial margin value corresponding to the high-risk level, the fifth initial margin value corresponding to the medium-risk level, and the sixth initial margin value corresponding to the low-risk level.

[0106] S312, based on the ship density distribution map of the quarterly layer, extract seasonal fluctuation grid cells and determine the first residual fluctuation value of the seasonal fluctuation grid cells.

[0107] Furthermore, by comparing the quarterly ship density distribution map with the annual comprehensive ship density distribution map, grid cells whose ship dynamic density in a specific quarter is significantly higher than the annual average ship dynamic density are identified and denoted as seasonal fluctuation grid cells. The first margin fluctuation value is generally taken as 0.3 meters, but it can be adjusted to other values ​​according to actual needs; this invention does not limit this.

[0108] S313, extract emergency fluctuation grid cells based on the ship density distribution map of the event-driven layer, and determine the second residual fluctuation value of the emergency fluctuation grid cells.

[0109] Furthermore, based on the ship density distribution map of the event-driven layer corresponding to a specific event period, by judging the relationship between the ship dynamic density during the specific event period and the annual average ship dynamic density, if the ship dynamic density of a certain grid cell spikes sharply, then that grid cell is identified as an emergency fluctuation grid cell. The second margin fluctuation value is generally taken as 0.7 meters, but it can also be adjusted to other values ​​according to actual needs; this invention does not limit this.

[0110] S314, calculate the basic value of the margin for each grid cell based on the initial value of the margin, the first margin fluctuation value, and the second margin fluctuation value.

[0111] Furthermore, the baseline value of the margin is the sum of the initial value of the margin, the first margin fluctuation value, and the second margin fluctuation value.

[0112] The above method transforms the burial depth safety margin from a static assignment process to a multi-factor, hierarchically weighted dynamic calculation process in terms of time and space. By using the ship density distribution map of the annual comprehensive layer, different initial margin values ​​are assigned to grid cells of different densities. At the same time, a quarterly layer and an event-driven layer are introduced to identify seasonal fluctuation grid cells and emergency fluctuation grid cells, and correspondingly increase the first margin fluctuation value and the second margin fluctuation value, thereby realizing the "time dynamic" adjustment of the safety margin and accurately responding to peak risks.

[0113] S32, based on the ship density distribution map, extract the representative ships and their occurrence frequency for each grid cell, and determine the margin variation coefficient for each grid cell based on the occurrence frequency of the representative ships.

[0114] Furthermore, the representative vessel refers to the type of vessel with the largest tonnage appearing in each grid cell. For each grid cell, the vessel information within that grid cell is analyzed based on the vessel AIS data. That is, all vessels that have appeared in each grid cell are analyzed, and the vessel type with the largest tonnage is selected as the representative vessel type for each grid cell. The frequency of occurrence of the representative vessel type is then determined. For example, if a 100,000-ton cargo ship frequently anchors in a certain grid cell, even if there are more fishing boats, that cargo ship is still considered the representative vessel type. The frequency of occurrence refers to the probability or frequency of the representative vessel type appearing within the statistical period. For example, during a typhoon, an average of two large cargo ships are anchored in that grid cell per day.

[0115] In some embodiments, the representative vessel refers to the vessel type with the largest tonnage appearing in each grid cell; determining the margin variation coefficient of each grid cell based on the frequency of occurrence of the representative vessel includes: S321, converting the frequency of occurrence of the representative vessel into the number of occurrences with a quarter as the statistical window; S322, calculating the average frequency of occurrence of the representative vessel type in all grid cells, and calculating the relative frequency of the representative vessel based on the average value and the number of occurrences; wherein, the relative frequency is equal to the quotient of the number of occurrences divided by the average value. For example, if a grid cell has 15 bulk carriers of 100,000 tons or more anchored in the third quarter, then the number of occurrences with a quarter as the statistical window is 15 times / quarter. If the average frequency of occurrence of 100,000-ton bulk carriers in the entire target sea area is 10 times / quarter, then the relative frequency = 15 / 10 = 1.5.

[0116] S323, determine the margin variation coefficient based on the mapping relationship between relative frequency and margin variation coefficient.

[0117] The mapping relationship between the relative frequency and the margin variation coefficient includes: if the relative frequency > 3, the margin variation coefficient is 1.5; if 1.5 < relative frequency ≤ 3, the margin variation coefficient is 1.2; if 0.5 < relative frequency ≤ 1.5, the margin variation coefficient is 1.0; if 0.1 < relative frequency ≤ 0.5, the margin variation coefficient is 0.9; and if the relative frequency ≤ 0.1, the margin variation coefficient is 0.8.

[0118] S33, Calculate the burial depth safety margin based on the basic margin value and the margin variation coefficient.

[0119] Wherein, the burial depth safety margin is the product of the margin base value and the margin variation coefficient.

[0120] The method described above for generating the burial depth safety margin for each grid cell introduces the first and second margin fluctuation values ​​corresponding to the quarterly and event-driven layers based on the initial margin value. This achieves spatially differentiated configuration and time-dynamic adjustment of the safety margin, solving the problem that static design cannot cope with short-term high risks. By calculating the margin variation coefficient based on the representative ship type with the largest tonnage and its frequency of occurrence, it ensures that the safety design aims to resist the greatest possible threat in the area, avoiding underestimation of risk due to the large number of small ships. At the same time, the probability of occurrence is quantified by "relative frequency" and a nonlinear mapping relationship is established with the margin variation coefficient. The risk coefficient of the most frequently occurring threat is significantly amplified. Thus, the determination of the burial depth safety margin comprehensively considers the three major factors of static risk, dynamic fluctuation, and threat intensity, greatly improving the objectivity, consistency, and transparency of decision-making.

[0121] Figure 4 is a schematic diagram of a subsea cable burial depth determination system provided by the present invention. Referring to Figure 4, the system 400 includes: a data collection module 410, used to divide the target sea area into grid cells according to the initial route of the subsea cable, and collect multi-source data of the target sea area, the multi-source data including at least: marine environmental data, ship AIS data, anchor data, and other human activity data; a first analysis module 420, used to construct a multi-timescale ship density distribution map based on the ship AIS data, the time scale including at least annual, quarterly, or event-driven; a second analysis module 430, used to establish a finite element simulation model of the coupled anchor body-anchor chain system based on the marine environmental data and the anchor data, and use the finite element simulation model to calculate the maximum penetration depth of each grid cell; and a burial depth calculation module 440, used to generate a burial depth safety margin for each grid cell along the initial route of the subsea cable according to the multi-timescale ship density distribution map, and calculate a recommended burial depth value in combination with the maximum penetration depth.

[0122] In some embodiments, the submarine cable burial depth determination system further includes a burial depth correction module, used to correct the recommended burial depth value and output a final burial depth value by combining geological feasibility, other human activity data, and equipment capabilities.

[0123] For a detailed description of the submarine cable burial depth determination system described above, please refer to the description of the relevant method steps in the above embodiments; repeated details will not be repeated. The embodiments of the submarine cable burial depth determination method and system described above are merely illustrative. The "units" and "modules" used as separate components can be combinations of software and / or hardware that implement a predetermined function, and may or may not be physically separate. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0124] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for determining the burial depth of a submarine cable, characterized in that, The method includes: dividing the target sea area into grid cells according to the initial route of the submarine cable, and collecting multi-source data of the target sea area, including at least: marine environmental data, ship AIS data, anchor data, and other human activity data; constructing a multi-timescale ship density distribution map based on the ship AIS data, including at least annual, quarterly, or event-driven timescales; establishing a finite element simulation model of the coupled anchor body-anchor chain system based on the marine environmental data and the anchor data, and calculating the maximum penetration depth of each grid cell using the finite element simulation model; generating a burial depth safety margin for each grid cell along the initial route of the submarine cable according to the multi-timescale ship density distribution map, and calculating a recommended burial depth value in combination with the maximum penetration depth.

2. The method for determining the burial depth of submarine cables as described in claim 1, characterized in that, The process of constructing a multi-timescale ship density distribution map based on the ship AIS data includes: classifying and marking ship activities in all grid cells according to the ship AIS data to obtain no-anchorage zones and non-no-anchorage zones; calculating the ship dynamic density in the spatiotemporal dimension for each grid cell in the non-no-anchorage zone; and generating a multi-timescale ship density distribution map based on the ship dynamic density in the spatiotemporal dimension for each grid cell.

3. The method for determining the burial depth of submarine cables as described in claim 2, characterized in that, The non-restricted anchorage zone includes anchorage areas and navigation areas. Calculating the ship dynamic density in the spatiotemporal dimension for each grid cell within the non-restricted anchorage zone includes: for each grid cell in the anchorage area, calculating the ship dynamic density according to a first formula, where the first formula is: For each grid cell in the navigation area, the ship dynamic density is calculated according to the second formula, which is: Among them, the first weight coefficient is the ship type weight, the second weight coefficient is the anchoring risk weight, and the third weight coefficient is the towing risk weight.

4. The method for determining the burial depth of submarine cables as described in claim 1, characterized in that, The finite element simulation model includes: a drop anchor simulation model and a towed anchor simulation model; the establishment of a coupled anchor-anchor chain system finite element simulation model based on the marine environment data and the anchor data includes: obtaining the basic parameters required for modeling based on the marine environment data and the anchor data; based on the basic parameters, establishing the drop anchor simulation model and the towed anchor simulation model respectively in the finite element simulation environment using a fluid-structure interaction method, wherein the fluid-structure interaction method refers to establishing a computational fluid dynamics model that includes the anchor body, anchor chain, and seabed soil and simulating the fluid domain around the anchor body, and performing bidirectional data exchange; and calibrating and verifying the drop anchor simulation model and the towed anchor simulation model through physical experiments and field measurements.

5. The method for determining the burial depth of submarine cables as described in claim 4, characterized in that, In the fluid-structure interaction method, the seabed soil model adopts a generalized plastic constitutive model that can reflect the soil strain rate effect and the strength degradation under cyclic loading.

6. The method for determining the burial depth of submarine cables as described in claim 4, characterized in that, The calculation of the maximum penetration depth of each grid cell using the finite element simulation model includes: extracting representative ships for each grid cell based on the ship density distribution map, and extracting matching anchor parameters from the anchor data based on the representative ships, wherein the representative ships refer to the ship type with the largest tonnage appearing in each grid cell; obtaining seabed geological parameters for each grid cell based on the marine environmental data; inputting the anchor parameters and seabed geological parameters of each grid cell into the anchor dropping simulation model and the anchor dragging simulation model respectively to obtain the anchor dropping impact depth and the anchor dragging plowing depth; and taking the larger of the anchor dropping impact depth and the anchor dragging plowing depth as the maximum penetration depth of the current grid cell.

7. The method for determining the burial depth of submarine cables as described in claim 6, characterized in that, The recommended burial depth value is the sum of the burial depth safety margin and the maximum penetration depth; the step of generating the burial depth safety margin for each grid cell along the initial route of the submarine cable based on the multi-timescale ship density distribution map includes: determining the basic margin value for each grid cell based on the multi-timescale ship density distribution map; extracting the representative ships and their occurrence frequencies for each grid cell based on the ship density distribution map, and determining the margin variation coefficient for each grid cell based on the occurrence frequency of the representative ships; and calculating the burial depth safety margin based on the basic margin value and the margin variation coefficient for each grid cell.

8. The method for determining the burial depth of submarine cables as described in claim 7, characterized in that, The multi-timescale ship density distribution map includes at least annual comprehensive layer, quarterly layer, and event-driven layer ship density distribution maps; determining the margin base value of each grid cell based on the multi-timescale ship density distribution map includes: determining the initial margin value of each grid cell based on the annual comprehensive layer ship density distribution map; extracting seasonal fluctuation grid cells based on the quarterly layer ship density distribution map and determining the first margin fluctuation value of the seasonal fluctuation grid cells; extracting emergency fluctuation grid cells based on the event-driven layer ship density distribution map and determining the second margin fluctuation value of the emergency fluctuation grid cells; and calculating the margin base value of each grid cell based on the initial margin value, the first margin fluctuation value, and the second margin fluctuation value.

9. The method for determining the burial depth of submarine cables as described in claim 1, characterized in that, The method further includes: adjusting the recommended burial depth value by combining geological feasibility, other human activity data, and equipment capabilities, and outputting the final burial depth value.

10. A system for determining the burial depth of a submarine cable, characterized in that, The system includes: a data collection module for dividing the target sea area into grid cells according to the initial route of the submarine cable and collecting multi-source data of the target sea area, including at least marine environmental data, ship AIS data, anchor data, and other human activity data; a first analysis module for constructing a multi-timescale ship density distribution map based on the ship AIS data, including at least annual, quarterly, or event-driven timescales; a second analysis module for establishing a finite element simulation model of the coupled anchor body-anchor chain system based on the marine environmental data and the anchor data, and calculating the maximum penetration depth of each grid cell using the finite element simulation model; and a burial depth calculation module for generating a burial depth safety margin for each grid cell along the initial route of the submarine cable according to the multi-timescale ship density distribution map, and calculating a recommended burial depth value in conjunction with the maximum penetration depth.

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