Novel trailing suction hopper dredger with height-automatically-adjustable energy dissipation device and loading construction operation method of novel trailing suction hopper dredger

Abstract

According to the novel trailing suction dredger with the height of the energy dissipation device capable of being automatically adjusted and the loading construction operation method of the novel trailing suction dredger, an original ship of the trailing suction dredger is transformed or a new ship is built, and the height-adjustable energy dissipation device is arranged on hardware; and the height-adjustable energy dissipation device is managed by utilizing a shipborne loading control system on software, so that loading construction operation is realized. The height of the energy dissipation device can be automatically and flexibly adjusted, and the loading efficiency and the loading flatness of silt in the cabin are improved by reducing overflow loss.

Description

[0001] The present application is a division of Chinese Patent Application "Method for Automatically Adjusting and Optimizing the Height of an Energy Dissipation Device of a Trailing Suction Dredger", Application No. 202411411313.6 TECHNICAL FIELD

[0002] The present application belongs to the technical field of dredging engineering, and particularly relates to an automatic adjusting and loading method for an energy dissipation system of a trailing suction dredger. TECHNICAL BACKGROUND

[0003] A trailing suction dredger is a main ship in the dredging industry and plays an important role in channel dredging, reclamation, and port maintenance projects. The mud tank system is an important part of the trailing suction dredger and is responsible for the important functions of dredging and loading, and flushing and discharging. The loading construction process of the trailing suction dredger can be divided into loading and overflow according to the characteristics of different stages. According to the target soil characteristics, the slurry (a mixture of water and sediment) continuously flows into the mud tank through the inlet pipe, part of the sediment deposits at the bottom of the tank under the action of gravity, and the other part of the sediment and water are mixed in the tank in a suspended state. When the liquid level of the water and sediment mixture exceeds the height of the overflow cylinder, different degrees of overflow loss occur.

[0004] The loading and overflow construction efficiency of the trailing suction dredger is directly related to the design and arrangement of the energy dissipation device. At present, the energy dissipation device of most domestic trailing suction dredgers is fixedly designed and cannot adjust the height of the energy dissipation device according to different soil, slurry concentration, and other complex working conditions, so as to reduce the disturbance of the inlet water flow to the sediment in the tank. When the sediment particles are relatively coarse, the sediment deposits quickly, and if the installation height of the energy dissipation device is too low, the outlet will be easily blocked. When the sediment particles are relatively fine, if the installation height of the energy dissipation device is too high, the fine-grained sediment will be disturbed under the action of the inlet water flow, so that most of the fine-grained sediment is in a suspended state, increasing the overflow loss and reducing the loading efficiency, and also adversely affecting the surrounding construction water environment. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a height-adjustable energy dissipation device for a trailing suction dredger, a height automatic adjusting and optimizing method, and a ship-mounted system, which can automatically and flexibly adjust the height of the energy dissipation device during the construction process of the trailing suction dredger, reduce the disturbance of the sediment in the tank as much as possible, reduce the overflow loss, improve the loading flatness and loading efficiency of the sediment in the tank, and meet the needs of different soil, inlet concentration, inlet flow, trailing suction ship mud tank structure size, and other working conditions.

[0006] TECHNICAL SCHEME

[0007] One of the objects of the present application is to provide a method for automatically adjusting and optimizing the height of an energy dissipation device of a trailing suction dredger, comprising:

[0008] Process one: constructing a height-adjustable energy dissipation device in the tank of the trailing suction dredger;

[0009] Process two determines the optimal energy dissipation height;

[0010] Step 1: Determine the core parameters through the existing data of the construction of the trailing suction hopper dredger, the geological survey report of the area to be constructed, and the soil data, etc. The core parameters include: geometric model, boundary condition, grid condition, initial condition, fluid motion and sediment motion. Specifically as follows:

[0011] (1) The geometric model mainly includes: the size of the hopper structure, the size of the transverse and longitudinal triangular tanks, the size of the overflow equipment, the size of the energy dissipation equipment and the height, and the position of the transverse and longitudinal triangular tanks, energy dissipation and overflow equipment relative to the hopper;

[0012] (2) The boundary conditions include: the inlet boundary is the loading flow and the loading slurry concentration, the overflow boundary is the free outflow boundary, the upper boundary of the hopper is the atmospheric pressure boundary, and the wall boundary is the wall boundary with a certain roughness;

[0013] (3) The grid condition includes: the grid range in x, y, z directions and the unit grid size.

[0014] (4) The initial conditions include: the initial water level H0, the loading simulation time T;

[0015] (5) The fluid motion parameters include: fluid temperature T, fluid viscosity μ, fluid motion equation.

[0016] (6) The fluid motion equation selects the RNG k-ε equation according to the loading characteristics, specifically as follows:

[0017]

[0018] In the formula: k——turbulent kinetic energy;

[0019] u i ——velocity component;

[0020] x i , y i ——coordinate components;

[0021] μ——molecular viscosity coefficient;

[0022] μ t ——turbulent viscosity coefficient;

[0023] G k ——turbulent kinetic energy generation term;

[0024] ε——turbulent kinetic energy dissipation rate;

[0025] α k , α ε ——k, ε turbulent Prandtl number;

[0026] where C 1ε = 1.42, η0= 4.377, β = 0.012;

[0027] where C 2ε = 1.68.

[0028] The parameters of sediment transport include sediment size, sediment density, sediment porosity, critical Shields number, angle of repose, bed load transport coefficient and erosion coefficient, which are related to four types of sediment transport: sediment suspension, sediment deposition, sediment erosion and sediment bed load transport. The following empirical formulas are used to calculate the type of sediment transport for each sediment particle in the simulation process.

[0029] where the empirical formula of Mastbergen and Von den Berg is used to calculate the sediment incipient motion and erosion process.

[0030]

[0031] where α is the entrainment coefficient, n s is the outward normal direction of the bed surface, θ is the Shields number of the sediment particle, θ cr is the critical Shields number of the sediment particle, g is the acceleration of gravity, μ is the dynamic viscosity of the fluid, d s is the sediment size, ρ s is the sediment density, and ρ f is the fluid density.

[0032] The expression of the Shields number θ of the sediment particle is:

[0033]

[0034] where τ is the shear stress on the riverbed surface.

[0035] In the non-horizontal bed surface area, the critical Shields number is corrected by considering the effect of the sediment angle of repose, and the corrected value θ cr,i ’ is

[0036]

[0037] where κ is the angle between the vertical line of the deposition surface and the acceleration of gravity g; φ is the angle of repose of the sediment; and ψ is the angle between the fluid uphill direction and the flow direction.

[0038] The empirical formula of equati is used to calculate the bed load transport process in the simulation process.

[0039]

[0040] wherein the calculation formula of the bed load thickness δ is:

[0041]

[0042] Therefore, the calculation formula of the bed load transport velocity is:

[0043]

[0044] Step 2: Perform the loading process simulation prediction, including the establishment of a loading numerical model and loading simulation prediction.

[0045] Establishing a loading numerical model: according to the input core parameters, using a CFD software (prior art) to establish a numerical model capable of simulating the loading construction process, so as to realize the loading simulation function.

[0046] Loading simulation prediction: using the above loading numerical model, setting different energy dissipation device height position conditions, performing numerical simulation, simulating the entire loading process, realizing the simulation prediction of the loading capacity, earthwork, total overflow loss and sediment deposition height in the tank with the change of loading time, and obtaining multiple sets of numerical simulation calculation results corresponding to different energy dissipation device height positions. The energy dissipation device height position needs to be manually set.

[0047] The numerical simulation calculation results also include: t (flow rate at time t three-dimensional grid point cloud); p t (density at time t three-dimensional grid point cloud); v x (x direction component velocity at time t three-dimensional grid point cloud); v y (y direction component velocity at time t three-dimensional grid point cloud). The numerical calculation results are provided to step 3.

[0048] Step 3: Based on the numerical simulation results, setting the evaluation basis order according to the four indexes of loading capacity, earthwork, overflow loss and sediment deposition flatness, and obtaining the optimized recommended height of the energy dissipation device;

[0049] In the multiple sets of numerical simulation results, different energy dissipation device heights correspond to different loading capacity, earthwork, overflow loss and sediment deposition flatness, and the evaluation basis order is set. According to the evaluation basis order (first gradient, second gradient), the optimized design recommended value of the energy dissipation device height is determined. Usually, the loading efficiency represented by the loading capacity, earthwork and overflow loss is taken as the first gradient discrimination standard, and the sediment deposition flatness is taken as the second gradient discrimination standard. Among them, the greater the loading capacity and earthwork, the smaller the overflow loss, and the higher the sediment deposition flatness, the better the influence of the energy dissipation device height of this working condition on the loading effect.

[0050] Preferably, the optimization target is set as the optimal deposition sediment flatness a and the maximum earthwork D, and the optimization model objective function is:

[0051]

[0052] max D = max∑ΔQ i ·Δt·ρ (16)

[0053] Set the constraint conditions (x.t.):

[0054] X = {x1, x2, x3…, x i} (17)

[0055] Wherein, Δt is the length of the time period for calculating the deposition earthwork; ΔQ i is the outflow in the Δt time period; ρ is the outflow concentration in the Δt time period; x i belongs to [0, H], H represents the height of the hold, x (it) as a parameter for calculating the flatness, represents the deposition sediment height measured at the sampling position i at time t, represents the average value of the deposition sediment height of the longitudinal center axis section of the hold.

[0056] t < T (18)

[0057] In the formula, T represents the maximum time set initially.

[0058] Set multiple groups of energy dissipation device heights, respectively calculate q t , ρ t , v x and v y by using the numerical calculation model in step 2, and then calculate the deposition sediment flatness and the earthwork, and select the best one according to the above optimization target (optimal flatness and maximum earthwork), and the corresponding energy dissipation device height is the optimal energy dissipation device height.

[0059] Considering the time and computing power, according to the relevant numerical calculation and prediction experience, the number of energy dissipation device height groups is suggested to be 12-20, the interval between each group is 0.25-0.5m, and the height variation range is 5-6m.

[0060] Process three with optimal energy dissipation height for loading

[0061] Step 4: According to the optimal energy dissipation device height obtained in step 3, adjust the hydraulic support rod of the adjustable height energy dissipation device, and raise or lower the energy dissipation device height to the optimal height.

[0062] Further, in step 3, in order to avoid complex numerical calculation process, a neural network is introduced for predicting the deposition sediment height and the earthwork. As follows:

[0063] A deposition sediment height prediction model is established for predicting the deposition sediment height as follows:

[0064] The calculation of X is performed by establishing a prediction model of X(t) value and numerical simulation initial conditions and boundary conditions as follows:

[0065] Input value: q t is a three-dimensional grid point cloud of flow rate at time t; p t is a three-dimensional grid point cloud of density at time t; v x is a three-dimensional grid point cloud of x-direction component velocity at time t; v y is a three-dimensional grid point cloud of y-direction component velocity at time t.

[0066] Output value: the deposition sediment height matrix of the flatness section calculated at the next time interval of At is denoted as X(t+At), which is the label item of the deposition sediment height prediction model. The three-dimensional position of the energy dissipation device is set to 0, which represents the spatial characteristics of the energy dissipation device.

[0067] The numerical simulation calculated q t , p t , v x , v y of each time are extracted at a time interval of At, respectively. t , p t , v x , v y The three-dimensional grid data corresponding to t+At are combined as a label matrix X for calculating the value of the deposition sediment height in the cabin, and the network is trained. Through the above operation, the deposition sediment height prediction model of the calculation points on the flatness calculation plane is obtained by applying numerical simulation data training.

[0068] In the training stage, the input and label are obtained by the loading process simulation prediction model in step 2; after training, the deposition sediment height of each point is predicted according to the measured q t , p t , v x , v y , and the flatness of the deposition sediment is reflected.

[0069] A soil volume prediction model is established for predicting the soil volume in the cabin as follows:

[0070] As above, dt is a three-dimensional grid point cloud of soil volume at time t, and d(t+At) represents the soil volume calculated at the next time interval of At as the label item of the soil volume prediction model. The q t , p t , v x , v yThe data and the network of the three-dimensional data of the earthwork volume in the mud tank at the time t+Delta t are used to train an earthwork volume prediction model.

[0071] According to the prediction model, the order of the two evaluation bases of the earthwork volume and the flatness is set, and a recommended optimal height is obtained.

[0072] The second object of the present application provides a height optimization system for an energy dissipation device carried by a drag suction dredger, characterized in that it comprises a core parameter input module, a simulation and prediction module for the loading process, a design optimization output module, and a height automatic adjustment module, and these software modules are embedded in and called by a shipboard loading control system.

[0073] The core parameter input module comprises:

[0074] The core parameters include a geometric model, boundary conditions, grid conditions, initial conditions, fluid motion and sediment motion. The geometric model includes the size of the mud tank structure, the size of the transverse and longitudinal triangular tanks, the size of the overflow equipment, the size of the energy dissipation equipment and the height, and the position of the transverse and longitudinal triangular tanks, the energy dissipation and overflow equipment relative to the mud tank. The boundary conditions include the loading flow and the loading slurry concentration of the inlet boundary, the free outflow boundary of the overflow boundary, the atmospheric pressure boundary of the upper boundary of the mud tank, and the wall boundary with a certain roughness of the tank wall boundary. The grid conditions include the grid range in x, y and z directions and the unit grid size. The initial conditions include the initial water level H0 and the loading simulation time t. The fluid motion parameters include fluid temperature T, fluid viscosity mu and fluid motion equation. The sediment motion parameters mainly include sediment particle size, sediment density, sediment porosity, critical Hillz number, underwater rest angle, transport motion coefficient and scour coefficient, involving four motion forms of sediment suspension, sediment deposition, sediment scouring and sediment transport.

[0075] The simulation and prediction module for the loading process comprises:

[0076] Using the parameters input by the core parameter input module, numerical calculation is performed to simulate the loading process under different working conditions. The simulation and prediction module for the loading process realizes simulation and prediction of the loading process, including two parts of establishing a loading numerical model and loading simulation and prediction.

[0077] Establishing a loading numerical model: according to the input core parameters, a numerical model capable of simulating the loading construction process is established by using CFD software (prior art) to realize the loading simulation function.

[0078] Chamber simulation prediction: using the above-mentioned chamber numerical model, set different energy dissipation device height position conditions, carry out numerical simulation, simulate the whole chamber loading process, realize the simulation prediction of the change of loading capacity, earthwork, total overflow loss and sediment deposition height in the chamber with the chamber loading time, and obtain a plurality of numerical simulation calculation results corresponding to different energy dissipation device height positions. The energy dissipation device height position needs to be manually set.

[0079] The numerical simulation calculation results also include: q t (t three-dimensional grid point cloud of flow rate at time t); p t (t three-dimensional grid point cloud of density at time t); v x (t three-dimensional grid point cloud of x-direction component velocity at time t); v y (t three-dimensional grid point cloud of y-direction component velocity at time t). The results of numerical calculation are provided to the design optimization output module.

[0080] This module can display various data in the calculation process in real time, and present the simulation results in a visual manner in the three-dimensional model. Users can have a more intuitive and in-depth understanding of the chamber loading process by viewing the specific flow rate, concentration and earthwork under each condition. It is helpful for users to analyze various phenomena in the chamber loading process, such as flow rate distribution and sediment concentration change, and further optimize the chamber loading scheme.

[0081] Among them, the design optimization output module:

[0082] Based on the numerical simulation results output by the chamber process simulation prediction module, the evaluation basis sequence is set according to the four indicators of loading capacity, earthwork, overflow loss and sediment deposition flatness, and the optimized recommended height of the energy dissipation device is obtained; users can click to select the evaluation basis sequence (chamber efficiency, flatness) according to actual needs; the system will automatically output the optimized recommended value of the height of the energy dissipation device according to the evaluation basis selected by the user.

[0083] Specifically, in a plurality of numerical simulation results, different energy dissipation device heights correspond to different chamber loading capacity, earthwork, overflow loss and sediment deposition flatness, the evaluation basis sequence is set, and the optimized design recommended value of the height of the energy dissipation device is generated according to the evaluation basis sequence (first gradient, second gradient). Usually, the chamber efficiency represented by the loading capacity, earthwork and overflow loss is taken as the first gradient discrimination standard, and the sediment deposition flatness is taken as the second gradient discrimination standard. Among them, the greater the loading capacity and earthwork, the smaller the overflow loss, and the higher the sediment deposition flatness, the better the effect of the height of the energy dissipation device on the chamber loading.

[0084] Among them, the height automatic adjustment module:

[0085] Based on the energy dissipation device optimization height recommended value output by the design optimization output module, a control signal is sent through the ship-mounted loading control system to automatically control the hydraulic support rod on the adjustable height energy dissipation device. By accurately controlling the extension and retraction of the hydraulic support rod, the height of the energy dissipation device is automatically and accurately adjusted. In addition, the user can also manually determine the soil condition of the construction area through the existing geological survey data, and input the appropriate height of the energy dissipation device through the loading control system according to engineering experience. After receiving the instruction, the system sends a control signal to the hydraulic support rod to realize the manual assisted lifting adjustment of the energy dissipation device. This adjustment method is more flexible and can adapt to different construction environments and needs.

[0086] The beneficial effect of the present application is to provide a cutter suction dredger energy dissipation device height automatic adjustment optimization method and height optimization system, which can automatically and accurately adjust the height of the energy dissipation device in real time according to different soil and different slurry concentration requirements during construction. The energy dissipation device will not be too low to cause the coarse particle sediment to block the outlet of the energy dissipation device, nor will it be too high to cause the water flow to disturb the sediment and increase the suspended sediment overflow loss. By accurately controlling the height of the energy dissipation device, the construction efficiency of the cutter suction dredger is improved, and the adverse effects of loading overflow on the construction water environment are reduced, which has engineering application value. BRIEF DESCRIPTION OF DRAWINGS

[0087] Figure 1 Front view of the adjustable height energy dissipation device of the example cutter suction dredger;

[0088] Figure 2 Side view of the adjustable height energy dissipation device of the example cutter suction dredger;

[0089] Figure 3 Schematic diagram of the telescopic pipe structure of the example;

[0090] Figure 4 Schematic diagram of the lifting hydraulic support rod structure of the example;

[0091] Figure 5 Three-dimensional modeling diagram of the mud tank of the example cutter suction dredger;

[0092] Figure 6 Mesh division condition of the three-dimensional model of the mud tank of the example cutter suction dredger;

[0093] Figure 7 Three-dimensional numerical simulation diagram of the mud tank of the example cutter suction dredger;

[0094] Figure 8 Flowchart of the sediment deposition height prediction model of the example;

[0095] Figure 9 Flowchart of the earthwork volume prediction model of the example;

[0096] Figure 10 Flow chart for adjustable height prediction for energy dissipation device optimization;

[0097] Figure 11 Simple artificial neural network prediction model for energy dissipation device optimization height;

[0098] Figure 12 Software module for energy dissipation device height optimization system for cutter suction dredger;

[0099] Figure 13 Automatic height adjustment process for energy dissipation device of cutter suction dredger during construction process;

[0100] Reference signs

[0101] 1 - telescopic main pipe, 2 - transverse pipe, 3 - connecting steel plate, 4 - hydraulic support rod, 5 - inner beam in slurry tank, 6 - side wall of slurry tank;

[0102] 11 - inner pipe, 12 - outer pipe, 13 - filler, 14 - limit block, 15 - main pipe connecting flange;

[0103] 21 - outflow port, 22 - transverse pipe connecting flange;

[0104] 41 - rear cylinder cover, 42 - cylinder barrel, 43 - piston, 44 - piston rod, 45 - guide sleeve, 46 - sealing ring, 47 - front cylinder cover. DETAILED DESCRIPTION

[0105] The adjustable height energy dissipation device for cutter suction dredger, the height automatic adjustment optimization method and system of the present application will be further described in detail below in conjunction with the drawings.

[0106] Preparation process

[0107] When the cutter suction dredger is structurally modified, the structural part of the adjustable height energy dissipation device is as shown in Figures 1 to 4

[0108] The height adjustment of the energy dissipation device is embedded in the on-board loading control system and is controlled by it to adjust in time for optimal loading operation.

[0109] The adjustable height energy dissipation device for cutter suction dredger is composed of a telescopic main pipe 1, a transverse pipe 2, a connecting steel plate 3, a hydraulic support rod 4, and an inner beam 5 in the slurry tank. The inner beam 5 in the slurry tank is fixed to the side wall 6 of the slurry tank by welding technology. Four hydraulic support rods 4 for lifting are fixed on the inner beam 5 in the slurry tank by bolts. A connecting steel plate 3 is placed above the hydraulic support rod 4 and is fixed to the upper end of the hydraulic support rod 4 by bolts. The connecting steel plate 3 is connected to the outer pipe 12 of the telescopic main pipe 1 by welding.

[0110] ​The telescopic main pipe 1 is a sleeve structure, the inner pipe 11 and the outer pipe 12 are sealed by the filler 13 and do not affect the relative sliding, the limiting block 14 limits the telescopic amount of the telescopic main pipe 1, and the telescopic main pipe 1 can freely telescope within a certain limit under the action of the hydraulic support rod 4. The outer pipe 12 is connected with the transverse pipe 2 through the main pipe connecting flange 15.

[0111] The transverse pipe 2 is divided into left, middle and right three parts and is connected in sequence through flanges, and the transverse pipe 2 is provided with eight flow outlets 21 for energy dissipation and cabin loading of the slurry.

[0112] The hydraulic support rod 4 is composed of a rear cylinder cover 41, a cylinder barrel 42, a piston 43, a piston rod 44, a guide sleeve 45, a sealing ring 46 and a front cylinder cover 47. The rear cylinder cover 41 is connected with the mud cabin inner beam 5 through bolts and simultaneously seals the rear part of the cylinder barrel 42; the piston 43 is stressed in the cylinder barrel and transmits the stress to the upper connecting steel plate 3 through the piston rod 44; the guide sleeve 45 supports and guarantees the coaxiality of the piston rod 44 and the cylinder barrel 42; the front cylinder cover 46 and the piston rod 44 are sealed through the sealing ring 46, so as to prevent the water and silt in the loading process from affecting the normal work of the components in the cylinder barrel 42.

[0113] When the height of the energy dissipation device is adjusted, the ship-mounted loading control system controls the lifting of the four hydraulic support rods 4 in the embodiment, drives the outer pipe 12 of the telescopic main pipe 1 and the transverse pipe 2 to be lifted or lowered through the connecting steel plate 3, and the slurry is discharged into the mud cabin along the inner pipe 11, the outer pipe 12, the transverse pipe 2 and the flow outlet 21 to perform the loading operation.

[0114] Embodiment 1

[0115] Optimized implementation method for automatic adjustment of the height of the energy dissipation device of a trailing suction dredger

[0116] Process one refers to the preparation work for the facility modification of the trailing suction dredger. Details are not described herein.

[0117] Process two determines the optimal adjustment height value, including the following steps:

[0118] Step 1: determining the core parameters, including the key parameters of six parts of a geometric model, boundary conditions, mesh conditions, initial conditions, fluid motion and silt motion, which are used for automatically establishing a three-dimensional model of the mud cabin system and setting the scene constraint conditions of the loading simulation.

[0119] (1) The geometric model parameters include setting the dimensions of the mud cabin structure, the transverse and longitudinal triangular cabins, the overflow equipment, the energy dissipation equipment and the positions of the transverse and longitudinal triangular cabins and the energy dissipation and overflow equipment relative to the mud cabin, which are used for establishing a three-dimensional structure model of the mud cabin system. The model is established as shown in Figure 5 .

[0120] (2) Boundary conditions include setting the inlet boundary as the filling flow and the filling slurry concentration, selecting the overflow boundary as the free outflow boundary, the upper boundary of the slurry tank as the atmospheric pressure boundary, and the tank wall boundary as the wall boundary with a certain roughness;

[0121] (3) As shown in FIG. 3, the mesh is divided according to the three-dimensional model. The mesh conditions include setting the total mesh range in three directions containing the slurry tank system structure model, and setting the unit mesh size as appropriate length, width and height dimensions for identifying the slurry tank structure in the simulation calculation; Figure 6

[0122] (4) The initial conditions include setting the initial water level and the filling simulation time length;

[0123] (5) The fluid motion parameters include setting the fluid temperature and the fluid viscosity, and selecting the fluid motion equation as the RNG k-ε equation;

[0124] (6) The sediment motion parameters include setting the sediment particle size, the sediment density, the sediment porosity, the critical Hillz number, the underwater rest angle, the bed load transport coefficient and the scour coefficient, calculating the sediment incipient motion and scour process through the empirical formula of Mastbergen and Von den Berg, and calculating the bed load transport process in the simulation process through the empirical formula of equati.

[0125] Step 2: Establishing the filling numerical model and the filling simulation prediction;

[0126] Establishing the filling numerical model: referring to the input core parameters, using the CFD software to establish a numerical model capable of simulating the filling construction process, so as to realize the filling simulation function;

[0127] Filling simulation prediction: using the above filling numerical model, setting different energy dissipation device height position conditions, performing numerical simulation, simulating the entire filling process, realizing the simulation prediction of the filling capacity, the earthwork, the total overflow loss and the sediment height in the tank changing with the filling time, and obtaining a plurality of numerical simulation calculation results corresponding to different energy dissipation device height positions; the energy dissipation device height position needs to be manually set;

[0128] The numerical simulation calculation results also include: q t (three-dimensional grid point cloud of flow at time t); p t (three-dimensional grid point cloud of density at time t); v x (three-dimensional grid point cloud of x-direction component velocity at time t); v y (three-dimensional grid point cloud of y-direction component velocity at time t); the numerical calculation results are provided to Step 3.

[0129] ​The embodiment utilizes CFD software to automatically establish a numerical model of the packing construction process according to input core parameters, using a structured multi-block grid technique and a finite volume method, to realize simulation of the packing construction over time, with simulation results as shown in FIG. 8. Figure 7 The packing control system sets different sediment movement parameters according to the geological exploration report of the construction area and existing construction experience data for different soil types, and performs packing simulation calculation under multiple working conditions.

[0130] Step 3: Energy dissipation device height optimization output.

[0131] The optimization target is set to be optimal sediment deposition flatness α and maximum earthwork D, and the optimization model objective function is:

[0132]

[0133] max D = max∑ΔQ i ·Δt·ρ (16)

[0134] Set the constraint condition (x.t.):

[0135] X = {x1, x2, x3…, x i} (17)

[0136] Where Δt is the length of the time period for calculating the deposited earthwork; ΔQ i is the outflow in the Δt time period; and ρ is the outflow concentration in the Δt time period.

[0137] x i belongs to [0, H], H represents the height of the mud tank, and x (it) is a parameter for calculating flatness, representing the deposited sediment height measured by the sampling position i at time t, representing the average value of the deposited sediment height of the longitudinal central axis section of the mud tank.

[0138] t < T (18)

[0139] In the formula, T represents the maximum time initially set.

[0140] Set multiple groups of energy dissipation device heights, and calculate q t , ρ t , v x and v y using the numerical calculation model of step 2, and then calculate the deposited sediment flatness and earthwork, and select the best one according to the above optimization target (optimal flatness and maximum earthwork), and the corresponding energy dissipation device height is the optimal energy dissipation device height.

[0141] Optionally, the recommended design value for the energy dissipation device height can be determined based on the evaluation criteria (first-gradient, second-gradient) of four indicators: loading capacity, earthwork volume, overflow loss, and sediment flatness. Typically, loading efficiency, represented by loading capacity, earthwork volume, and overflow loss, is used as the first-gradient criterion, and sediment flatness as the second-gradient criterion. A higher loading capacity and earthwork volume, lower overflow loss, and higher sediment flatness indicate a better impact of the energy dissipation device height on the loading effect under that working condition.

[0142] Furthermore, in construction situations where the flatness of the loading compartment is highly critical, the order of evaluation criteria can be adjusted, with the flatness of the deposited sediment being used as the first priority.

[0143] In step 3, to avoid complex numerical calculations, a neural network is introduced to predict the height of sediment deposition and the volume of earthwork. (See below:)

[0144] Combination Figure 8 As shown, four variables are input into the input layer: qt (flow rate), ρt (density), vxt (x-direction velocity), and vyt (y-direction velocity). These input features are preprocessed by feature selection and standardization and then input into the target Transformer neural network model to obtain the predicted sediment height.

[0145] The target Transformer neural network model includes an Embedding Layer, Multi-head Attention, and Softmax (probability distribution output). The Embedding Layer vectorizes the input features, converting them into a vector representation suitable for network processing. This process maps high-dimensional input features to a low-dimensional vector space for subsequent processing. Multi-head Attention captures different feature information through multiple attention heads and integrates this information to weight the input features. Softmax calculates the probability distribution of each output based on the result of the multi-head attention mechanism.

[0146]

[0147] The output values ​​are mapped to the range [0,1], and the sum of the probabilities of all outputs is 1, which helps the model learn the non-linear relationship between the input features and the output results. Finally, the predicted sediment deposition height sequence (x1,x2,...,x) is output through the output layer. n ).

[0148] The Transformer neural network model (sediment deposition height prediction model) uses four input variables as training data and a sediment deposition height sequence as a label to train it. After each iteration, the loss function is calculated using validation data and its label. The mean squared error (MSE) is used as the loss function:

[0149]

[0150] where x i , are the iteratively calculated sediment deposition height and the true sediment deposition height as the label value, respectively.

[0151] The model adjusts the network weights using the backpropagation algorithm to minimize the loss function. In each training iteration, the gradient of the loss function is calculated, and the network weights are updated until the model reaches the preset convergence condition, obtaining the target neural network model.

[0152] As shown in Figure 9 , four variables are input into the input layer: qt (flow rate), pt (density), vxt (x-direction velocity), and vyt (y-direction velocity). The input features are preprocessed (normalized) and then input into the network. The BatchNorm layer calculates the mean and variance of all values in the mini-batch, and uses the calculated mean and variance to normalize each batch of data, so that the input of each layer maintains a relatively stable distribution, which speeds up the training and improves the stability of the model. The PointNet layer is a deep learning framework specifically designed to handle point cloud data. In this model, it is used to extract high-dimensional feature representations of input features. The fully connected layer further processes the features extracted from the PointNet layer, which can map high-dimensional features to the target output space, thereby achieving prediction of earthwork volume.

[0153] Alternatively, the present application also provides another more simple and fast energy dissipation device height optimization parameter recommendation method, which gives the optimal energy dissipation device height prediction process as shown in Figure 10 . The prediction process includes 10 parts: data input, data preprocessing, training set and test set division, neural network model building, forward propagation, loss function calculation, backpropagation, parameter update, model evaluation, and optimal value recommendation.

[0154] (1) Data input: As the starting point of the entire prediction model, qt (flow rate), pt (density), vxt (x-direction velocity), and vyt (y-direction velocity) of the mud entering the mud tank at time t, h (energy dissipation device height), and other data are input in table form.

[0155] (2) Data preprocessing: In this stage, the data described in (1) will be standardized. And calculate the earthwork D value and sediment flatness a value, set a new parameter λ (0 < λ < 1), calculate the λD-(1-λ)α value of each group of data

[0156]

[0157] D = ∑ΔQ i ·Δt·ρ (4)

[0158] In the formula: Δt is the length of the time period for calculating the deposited earthwork; ΔQ i is the outflow in the Δt time period; ρ is the outflow concentration in the Δt time period

[0159] (3) Training set and test set division: qt (flow rate), ρt (density), vxt (x-direction velocity) and vyt (y-direction velocity), h (energy dissipation device height) and other data will be divided into training set and test set. The training set is used to train the model, and the test set is used to evaluate the performance of the model. The division ratio is set to 8:2 or 7:3.

[0160] (4) Neural network model building: a simple artificial neural network (MLP) model is built as shown in Figure 11 . The neural network is composed of multiple layers of neurons (nodes), and each layer has several neurons. The layer structure includes the input layer (which receives the processed input data), the hidden layer (which performs complex calculations and extracts high-order features of the input data), and the output layer (which produces the final prediction result, i.e., the target function λD-(1-λ)α).

[0161] (5) Forward propagation: data from the input layer passes through each layer of neurons, calculates the activation function and outputs until the output layer. The calculation formula of each layer is as follows:

[0162] z (l) = W (l) a (l-1) +b (l) (5)

[0163] a (l) = σ(z (l) ) (6) In the formula: l is the number of activation layers; W (l) is the weight matrix; b (l) is the bias vector; a (l) and a (l-1) are the activation values of the current layer and the previous layer, respectively. In the input layer a can take the corresponding input data qt (flow rate), ρt (density), vxt (x-direction velocity) and vyt (y-direction velocity), h (energy dissipation device height) and other data for calculation; σ is the activation function.

[0164] Further, the activation function is selected as ReLU function:

[0165] σ(z (l) ) = ReLU(z (l) ) = max(0, z (l) ) (7)

[0166] (6) Loss function calculation: Select the common mean square error (MSE) as the loss function:

[0167]

[0168] In the formula: y i is the true value, is the predicted value, where y = λD - (1 - λ)α, n is the sample number.

[0169] (7) Back propagation: By calculating the gradient of the loss function with respect to each parameter, update the parameters to minimize the loss function. The gradient calculation formula is as follows:

[0170]

[0171] In the formula: δ (l) is the error term, which is the difference between the network predicted value and the true label value.

[0172] (8) Parameter update: Update the weight matrix and bias vector using the gradient descent optimization algorithm. The gradient descent update formula is as follows:

[0173]

[0174] In the formula: α is the learning rate.

[0175] (9) Model evaluation: Use the test set to evaluate the model performance with accuracy, precision, recall and other indicators.

[0176] (10) Optimal value recommendation: After the model training is completed, the input parameters qt (flow), ρt (density), vxt (x direction velocity) and vyt (y direction velocity), h (energy dissipation device height) and other parameters can be predicted. In order to find the maximum value of the model, fix the model parameters, and for each parameter in each layer, use the chain rule to calculate the derivative, make it equal to zero, find the extreme value candidate in a certain range, and select the maximum value, and obtain the optimal energy dissipation device height h by back propagation.

[0177] Process three with optimal energy dissipation height

[0178] Step 4: According to the optimal energy dissipation device height obtained in step 3, adjust the hydraulic support rod of the adjustable height energy dissipation device, and raise or lower the energy dissipation device height to the optimal height.

[0179] Embodiment 2

[0180] A trailing suction dredger on-board energy dissipation device height optimization system

[0181] The system comprises four developed software modules: a core parameter input module, a loading process simulation prediction module, a design optimization output module, and a high degree of automatic adjustment module, which are embedded in and called by a shipboard loading control system. Figure 12

[0182] The core parameter input module comprises:

[0183] The core parameters include geometric models, boundary conditions, grid conditions, initial conditions, fluid motion, and sediment motion.The geometric models include the size of the mud tank structure, the size of the transverse and longitudinal triangular tanks, the size of the overflow equipment, the size of the energy dissipation equipment and the height, and the position of the transverse and longitudinal triangular tanks and the energy dissipation overflow equipment relative to the mud tank. The boundary conditions include the loading flow rate and the loading slurry concentration at the inlet boundary, the free outflow boundary at the overflow boundary, the atmospheric pressure boundary at the upper boundary of the tank, and the wall boundary with a certain roughness at the tank wall boundary. The grid conditions include the grid ranges in the x, y, and z directions and the unit grid size. The initial conditions include the initial water level H0 and the loading simulation time T. The fluid motion parameters include the fluid temperature T, the fluid viscosity μ, and the fluid motion equation. The sediment motion parameters mainly include the sediment particle size, the sediment density, the sediment porosity, the critical Hillz number, the underwater rest angle, the transport motion coefficient, and the scour coefficient, involving four motion forms of sediment suspension, sediment deposition, sediment scour, and sediment transport.

[0184] The loading process simulation prediction module comprises:

[0185] Using the parameters input by the core parameter input module, numerical calculation is performed to simulate the loading process under different conditions. The loading process simulation prediction module realizes loading process simulation prediction, including two parts: establishing a loading numerical model and loading simulation prediction.

[0186] Establishing a loading numerical model: according to the input core parameters, a numerical model capable of simulating the loading construction process is established using CFD software (prior art) to realize the loading simulation function.

[0187] Loading simulation prediction: using the above loading numerical model, different energy dissipation device height position conditions are set for numerical simulation to simulate the entire loading process, realize the simulation prediction of the loading capacity, earthwork volume, total overflow loss, and sediment height in the tank with the change of loading time, and obtain multiple sets of numerical simulation calculation results corresponding to different energy dissipation device height positions. The energy dissipation device height position needs to be manually set.

[0188] The numerical simulation calculation results also include: qt (t time flow of three-dimensional grid point cloud); p t (t time density of three-dimensional grid point cloud); v x (t time x direction of three-dimensional grid point cloud of partial velocity); v y (t time y direction of three-dimensional grid point cloud of partial velocity). The results of numerical calculation are provided to the design optimization output module.

[0189] The module can display various data in the calculation process in real time, and present the simulation results in a visual manner in the three-dimensional model. The user can have a more intuitive and in-depth understanding of the loading process by viewing the specific flow rate, concentration and earthwork volume and other output results under various working conditions. It is helpful for the user to analyze various phenomena in the loading process, such as flow rate distribution and sediment concentration change, and further optimize the loading scheme.

[0190] Among them, the design optimization output module:

[0191] Based on the numerical simulation results output by the loading process simulation prediction module, the evaluation basis sequence is set according to four indexes of loading capacity, earthwork volume, overflow loss and sediment deposition flatness, and the optimized recommended height of the energy dissipation device is obtained; the user can click to select the evaluation basis sequence (loading efficiency, flatness) according to actual needs; the system will automatically output the optimized recommended value of the height of the energy dissipation device according to the user's selection of the evaluation basis.

[0192] Specifically, in a plurality of numerical simulation results, different energy dissipation device heights correspond to different loading capacity, earthwork volume, overflow loss and sediment deposition flatness, and the evaluation basis sequence is set to determine the optimized design recommended value of the height of the energy dissipation device according to the evaluation basis sequence (first gradient, second gradient). Usually, the loading efficiency represented by the loading capacity, earthwork volume and overflow loss is taken as the first gradient discrimination standard, and the sediment deposition flatness is taken as the second gradient discrimination standard. Among them, the greater the loading capacity and earthwork volume, the smaller the overflow loss, and the higher the sediment deposition flatness, the better the effect of the height of the energy dissipation device on the loading effect.

[0193] Among them, the height automatic adjustment module:

[0194] Based on the energy dissipation device optimization height recommended value output by the design optimization output module, a control signal is sent via the ship-mounted loading control system to automatically control the hydraulic support rod on the adjustable height energy dissipation device. By precisely controlling the extension and retraction of the hydraulic support rod, automatic and precise adjustment of the height of the energy dissipation device is achieved. In addition, the user can also manually input the appropriate energy dissipation device height through the existing geological survey data to determine the soil conditions in the construction area, and according to engineering experience, input the appropriate energy dissipation device height through the loading control system. After receiving the instruction, the system sends a control signal to the hydraulic support rod to achieve manual assisted lifting adjustment of the energy dissipation device. This adjustment method is more flexible and can adapt to different construction environments and needs.

[0195] Each module is as follows:

[0196] The loading process simulation prediction module uses the parameters input in the core parameter input module to perform numerical simulation calculation on the loading process: the sediment is regarded as a solid particle, a fluid model and a sediment particle model are used to simulate four states of sediment suspension, deposition, resuspension and movement, and the outflow port of the energy dissipation device is separately partitioned for 2 times grid encryption using a partitioned block structured grid. The loading boundary is the loading flow and the loading slurry concentration, the overflow boundary is the free outflow boundary, the upper boundary of the mud tank is the atmospheric pressure boundary, and the tank wall boundary is the wall boundary with a certain roughness. The finite volume method is used to perform numerical simulation calculation on the loading process.

[0197] During the simulation process, this module can display various data such as flow rate, concentration, earthwork volume, etc. in real time, and present the simulation results in a visual manner in the three-dimensional model. Users can have a more in-depth and comprehensive understanding of the loading process through these intuitive data and images. In addition, users can also analyze various phenomena in the loading process, such as flow rate distribution and sediment concentration changes, by viewing the output results under various working conditions, to further optimize the loading scheme.

[0198] Further, the loading capacity, earthwork volume, overflow loss and deposition sediment flatness at different times during the loading process are calculated using the following formulas:

[0199] Loading capacity: represents the total mass of the slurry mixture loaded into the mud tank without overflowing.

[0200] M = M f + M ss + M sd

[0201] In the formula: M represents the loading capacity, M f represents the mass of the fluid in the tank, M ss represents the mass of the suspended sediment particles in the tank, M sd represents the mass of the deposited sediment particles in the tank.

[0202] Volume of earthwork: represents the volume of undisturbed soil loaded into the hopper without overflow.

[0203]

[0204] wherein ρ s represents the density of sediment particles, e represents the void ratio of undisturbed soil, and ρ f represents the density of fluid, ρ s1 represents the density of undisturbed soil.

[0205] Overflow loss: represents the total mass of slurry mixture loaded into the hopper but overflowed.

[0206] M l = M o - M

[0207] wherein M o is the total mass of slurry mixture flowing out of the outlet of the energy dissipation device.

[0208] Flatness in the hopper: represented by the standard deviation of the height of deposited sediment in the cross section of the longitudinal center axis of the hopper.

[0209]

[0210] wherein α represents the flatness in the hopper, x i represents the height of deposited sediment at position i in the cross section of the longitudinal center axis of the hopper, represents the average height of deposited sediment in the cross section of the longitudinal center axis of the hopper, and n represents the number of calculated heights of deposited sediment in the cross section of the longitudinal center axis of the hopper.

[0211] The height automatic adjustment module is a specific embodiment of the automation of the ship-mounted loading control system, which eliminates the process of manual adjustment of the height of the energy dissipation device. The module will automatically control the hydraulic support rod 4 set on the height-adjustable energy dissipation device according to the recommended value of the optimized height of the energy dissipation device obtained from the design optimization output module. Through precise control of the extension and retraction of the hydraulic support rod 4, real-time, automatic and accurate adjustment of the height of the energy dissipation device is realized. This automatic adjustment method not only improves the accuracy and efficiency of adjustment, but also reduces the difficulty and error of manual operation.

[0212] Further, the user can also input appropriate height of the energy dissipation device through the ship-mounted loading control system according to his own judgment and experience. After receiving the instruction, the system will send corresponding control signals to the hydraulic support rod 4 to realize manual auxiliary adjustment of the height of the energy dissipation device. This flexible adjustment method can adapt to different construction environments and needs, improving the adaptability and practicality of the system.

[0213] Example 3

[0214] A new type of cutter suction dredger with automatically adjustable energy dissipation device height and its method for loading operation A new type of cutter suction dredger with automatically adjustable energy dissipation device height and its method for loading operation

[0215] The height-adjustable energy dissipation device is managed by the ship-mounted loading control system, which has been introduced in embodiment 2.

[0216] Method for loading operation of cutter suction dredger with automatically adjustable energy dissipation device height

[0217] The specific process is as follows Figure 13 , including the following steps:

[0218] Step 1: The cutter suction dredger enters the construction area; manual input of core parameters before the start of construction, mainly including six parts of geometric model, boundary condition, grid condition, initial condition, fluid motion and sediment motion, and the specific content of the parameters is introduced in embodiment 1.

[0219] Step 2: The ship-mounted loading control system automatically establishes a numerical model of the loading construction process according to the input core parameters, realizing the simulation function of the loading construction changing with time.

[0220] Step 3: Set different energy dissipation device heights in the ship-mounted loading control system to perform loading simulation calculation under multiple working conditions.

[0221] Step 4: The design optimization parameter output module of the ship-mounted loading control system recommends the energy dissipation device height parameters. According to user requirements, select and set the evaluation basis sequence (first gradient, second gradient) and the number of recommended values, and automatically generate the recommended values of the energy dissipation device height optimization design. The core parameters of the energy dissipation device height position are recommended based on the default state, and the loading efficiency represented by the loading capacity, earthwork volume and overflow loss is taken as the first gradient discriminant standard, and the sediment deposition flatness is taken as the second gradient discriminant standard.

[0222] Further, in the construction condition with high requirement for loading flatness, the evaluation basis sequence can be adjusted, and the sediment deposition flatness is taken as the first gradient.

[0223] Step 5: When the position of the ship construction area and the excavation depth change greatly, refer to the geological exploration report, the excavation soil changes, and according to the updated input values of qt, ρt, vxt and vyt, repeat step 4 to recommend new energy dissipation device height optimization values.

[0224] Specifically, as the excavation progresses, the excavation position, depth, and soil conditions change. To improve overall loading efficiency, the loading control system changes the sediment movement parameters based on geological survey data, re-performs numerical calculations and neural network training processes such as loading simulation prediction under multiple working conditions, automatic optimization and recommendation of height parameters, and automatically controls the hydraulic support rod height using the loading control system, thereby adjusting the energy dissipation device height to ensure high loading efficiency at all times. When the fine particles in the excavated soil increase, the energy dissipation device height is automatically and accurately reduced to reduce the disturbance of the incoming water flow to the fine particle sediment, allowing the fine particles to quickly settle and reducing the loading overflow loss. When the coarse particles in the loaded slurry increase, the particles settle quickly, and the energy dissipation device height is automatically and accurately increased to prevent soil particles from clogging the energy dissipation device outlet 21.

[0225] Step 6: When the cutter suction dredger is working at different construction positions and excavation depths, the corresponding energy dissipation device height optimization recommendation value is called in combination with the ship position and the lowering depth of the rake arm, and a command is sent to the hydraulic support rod 4 set on the adjustable height energy dissipation device to realize real-time height adjustment of the energy dissipation device.

Claims

1. A novel trailing suction hopper dredger with automatically adjustable energy dissipation device height, characterized in that, The new trailing suction hopper dredger, through the modification of the original dredger or the construction of a new dredger, is equipped with an adjustable height energy dissipation device in terms of hardware, and the adjustable height energy dissipation device is managed by the shipboard loading control system in terms of software, thereby realizing loading construction operations.

2. A novel trailing suction hopper dredger with automatically adjustable energy dissipation device height as described in claim 1, characterized in that, The adjustable height energy dissipation device is designed to include a telescopic main pipe (1), a transverse pipe (2), a connecting steel plate (3), a hydraulic support rod (4), and a crossbeam inside the mud chamber (5). The telescopic main pipe (1) is a sleeve-type structure. The telescopic main pipe (1) includes an inner pipe (11), an outer pipe (12), filler (13), a limiting block (14), and a main pipe connecting flange (15). The inner pipe (11) and the outer pipe (12) are sealed by the filler (13). The limiting block (14) limits the telescopic range of the telescopic main pipe (1). The inner pipe (11) is connected to the mud conveying pipeline of the trailing suction dredger. The outer pipe (12) is connected to the transverse pipe (2) through the main pipe connecting flange (15). The transverse pipe (2) is divided into three parts: left, middle and right, which are connected in sequence through the transverse pipe connecting flange (22), and a total of 8 outlets (21) are provided; The crossbeam (5) inside the mud chamber is fixed to the side wall (6) of the mud chamber by welding technology. Four hydraulic support rods (4) for lifting are fixed to the crossbeam (5) inside the mud chamber by bolts. A connecting steel plate (3) is placed above the hydraulic support rod (4) and fixed to the upper end of the hydraulic support rod (4) by bolts. The connecting steel plate (3) is connected to the outer tube (12) of the telescopic main tube (1) by welding technology. Four hydraulic struts (4) are evenly arranged on the crossbeam (5) inside the mud chamber to ensure that the crossbeam (5) inside the mud chamber and the connecting steel plate (3) are subjected to uniform force while providing sufficient force. The hydraulic strut (4) consists of a rear cylinder head (41), a cylinder (42), a piston (43), a piston rod (44), a guide sleeve (45), a sealing ring (46), and a front cylinder head (47). The rear cylinder head (41) is bolted to the crossbeam (5) inside the mud tank, and at the same time seals the rear of the cylinder (42). The piston (43) is subjected to force inside the cylinder, which is transmitted to the connecting steel plate (3) above through the piston rod (44). The guide sleeve (45) supports and ensures the coaxiality of the piston rod (44) and the cylinder (42). The sealing ring (46) seals the front cylinder head (46) and the piston rod (44) to prevent water and mud from affecting the normal operation of the components inside the cylinder (42) during the loading process.

3. A novel trailing suction hopper dredger with automatically adjustable energy dissipation device height as described in claim 2, characterized in that, The shipboard loading control system is embedded with a core parameter input module, a loading process simulation and prediction module, a design optimization output module, and a height automatic adjustment module. By calling these modules, the height of the energy dissipation device of the trailing suction hopper dredger is automatically adjusted. Among them, the core parameter input module: The core parameters include geometric model, boundary conditions, mesh conditions, initial conditions, fluid motion, and sediment motion. The geometric model includes: the structural dimensions of the mud hopper, the dimensions of the transverse and longitudinal triangular hoppers, the dimensions of the overflow equipment, the dimensions and height of the energy dissipation equipment, and the relative positions of the transverse and longitudinal triangular hoppers and the energy dissipation overflow equipment to the mud hopper. The boundary conditions include the inlet boundary being the loading flow rate and mud concentration, the overflow boundary being the free outflow boundary, the upper boundary of the mud hopper being the atmospheric pressure boundary, and the hopper wall boundary being the wall boundary with a rough material. The mesh conditions include: the mesh range in the x, y, and z directions and the unit mesh size. The initial conditions include the initial water level H0 and the hopper loading simulation duration t. The fluid motion parameters include the fluid temperature T, the fluid viscosity μ, and the fluid motion equation. The sediment motion parameters include sediment particle size, sediment density, sediment porosity, critical Shields number, underwater angle of repose, bedload coefficient, and scour coefficient, involving four motion forms: sediment suspension, sediment deposition, sediment scour, and sediment bedload. Among them, the loading process simulation and prediction module: Using the parameters already input by the core parameter input module, numerical calculations are performed to simulate the loading process under different working conditions; the loading process simulation and prediction module realizes the simulation and prediction of the loading process, including two parts: establishing a loading numerical model and loading simulation and prediction. Establish a numerical model for loading: Based on the input core parameters, use CFD software to establish a numerical model that can simulate the loading process, so as to realize the loading simulation function. Loading simulation prediction: Using the above loading numerical model, set different working conditions for the height position of the energy dissipation device, and conduct numerical simulation to simulate the entire loading process. Realize the simulation prediction of the changes in loading volume, earthwork volume, total overflow loss and sediment height in the tank with loading time, and obtain multiple sets of numerical simulation calculation results corresponding to different height positions of the energy dissipation device; the height position of the energy dissipation device needs to be set manually. The numerical simulation results also include: a three-dimensional grid point cloud of the flow rate at time t, denoted as q. t The density of the three-dimensional mesh point cloud at time t, denoted as ρ. t The three-dimensional mesh point cloud of the x-axis velocity component at time t, denoted as v. x The three-dimensional mesh point cloud of the y-direction velocity component at time t, denoted as v. y The results of numerical calculations are provided to the design optimization output module. Among them, the design optimization output module: Based on the numerical simulation results output by the loading process simulation and prediction module, the evaluation criteria are set according to four indicators: loading volume, earthwork volume, overflow loss, and sediment flatness, to obtain the optimized recommended height of the energy dissipation device. Users can click to select the order of evaluation criteria according to actual needs. The system automatically outputs the optimized recommended value of the energy dissipation device height according to the evaluation criteria selected by the user. Among them, the automatic height adjustment module: Based on the recommended optimized height of the energy dissipation equipment output by the design optimization output module, a control signal is sent via the shipboard loading control system to automatically control the hydraulic struts on the adjustable-height energy dissipation equipment; by precisely controlling the extension and retraction of the hydraulic struts, the height of the energy dissipation equipment can be automatically and accurately adjusted.

4. A method for loading hoppers into a novel trailing suction hopper dredger with automatically adjustable height energy dissipation device as described in any one of claims 1-3, characterized in that... Includes the following steps: Step 1: The trailing suction hopper dredger enters the construction area; before construction begins, the core parameters are manually input, including six parts: geometric model, boundary conditions, mesh conditions, initial conditions, fluid motion, and sediment motion. Step 2: The shipboard loading control system automatically establishes a numerical model of the loading process based on the input core parameters, realizing the simulation function of loading changes over time. Step 3: Set different energy dissipation equipment heights in the shipboard loading control system and perform loading simulation calculations under multiple working conditions; Step 4: Recommend the height parameters of the energy dissipation equipment through the design optimization parameter output module of the shipboard loading control system; Step 5: When the location and excavation depth of the ship construction area change significantly, refer to the geological survey report and the corresponding changes in the excavated soil. Based on the updated input values ​​of flow rate, density, x-direction velocity and y-direction velocity, repeat Step 4 to recommend a new optimized value for the height of the energy dissipation equipment. Step 6: When the trailing suction hopper dredger is working at different construction locations and excavation depths, the corresponding energy dissipation equipment height optimization value is called in combination with the ship's position and the depth of the drag arm, and the command is sent to the hydraulic support rod (4) set on the adjustable height energy dissipation device to realize the real-time height adjustment of the energy dissipation device.

5. The loading and unloading operation method as described in claim 4, characterized in that, Step 4, Based on user needs, the order of evaluation criteria and the number of recommended values ​​are selected and set, and recommended values ​​for the optimal design of energy dissipation equipment are automatically generated; the order of evaluation criteria includes a first gradient and a second gradient. The recommended core parameters for the height and position of energy dissipation equipment are based on the following criteria: under the default conditions, the first-level criterion for judging the loading efficiency is represented by the loading capacity, earthwork volume, and overflow loss, and the second-level criterion is the flatness of the sediment. In construction situations where the flatness of the loading compartment is highly critical, the order of evaluation criteria is adjusted, with the flatness of the sediment as the first priority.

6. The loading and unloading operation method as described in claim 4, characterized in that, Step 5, As excavation progresses, the location and depth of the excavation change, and the soil conditions change. In order to improve the overall loading efficiency, the loading control system changes the sediment movement parameters based on the geological survey data, and re-performs the loading simulation prediction under multiple working conditions, automatic optimization of height parameters, and recommended numerical calculation and neural network training process. The loading control system automatically re-controls the height of the hydraulic struts, thereby adjusting the height of the energy dissipation device to always ensure high loading efficiency. When the amount of fine particles in the excavated soil increases, the height of the energy dissipation device is automatically and precisely reduced to reduce the disturbance of the incoming water flow to the fine particles of mud and sand, so that the fine particles settle quickly and reduce the overflow loss of the loading tank; when the amount of coarse particles in the loaded mud increases, the particles settle faster, and the height of the energy dissipation device is automatically and precisely increased to prevent soil particles from clogging the outlet of the energy dissipation device (21).

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