Prediction method and prediction device for overflow state of overflow cylinder and electronic equipment

Abstract

The invention provides a method and device for predicting the overflow state of an overflow cylinder and electronic equipment, and belongs to the technical field of dredging engineering.The method comprises the steps that a three-dimensional model of mud cabin fluid provided with the overflow cylinder is established; dividing fluid domain computational grids for the three-dimensional model; establishing a numerical calculation model of the mud cabin fluid for flow field calculation to obtain a flow field calculation result; and according to the flow field calculation result, extracting overflow state parameters of the overflow cylinder, and evaluating the overflow state. According to the prediction method provided by the invention, a numerical simulation method of fluid mechanics is adopted, the overflow state of the drag suction dredger in the mud cabin loading process is predicted, the overflow state parameters are obtained, quantitative indexes can be provided for evaluation of the overflow state, guidance is provided for optimization of the size of the overflow cylinder, and the engineering problem that the evaluation of the overflow effect lacks the quantitative indexes is solved; the loading efficiency of the trailing suction hopper dredger can be effectively improved, and dredging engineering benefits are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of dredging engineering, and particularly relates to a method and device for predicting the overflow state of an overflow cylinder, and an electronic device. Background Art

[0002] A trailing suction hopper dredger is an engineering ship equipped with a hopper system and a draghead device. It sucks the sediment mixture at the bottom of rivers and lakes through the draghead and stores it in the hopper, and is widely used in water projects such as channel dredging and port construction. As the core sediment storage unit of the hopper, an overflow device (such as an overflow cylinder) is provided inside, and its function is to discharge the low-concentration muddy water on the surface layer of the hopper to increase the sediment deposition concentration in the hopper, thereby improving the loading efficiency.

[0003] During the dredging process, low-density soil such as fine silt has a slow settlement rate and is easily leaked out of the ship along with the overflow water, thus forming an overflow loss, which not only reduces the construction energy efficiency, but also pollutes the water environment due to the diffusion of suspended sediment. Therefore, during the dredging construction process, the control of the overflow state of the overflow cylinder is crucial.

[0004] As a key component of the overflow system of modern trailing suction hoppers, the size design of the overflow cylinder directly affects the thickness of the overflow layer and the degree of sediment loss. If the diameter of the overflow cylinder is too large, the overflow speed will increase, and the sediment that has not been fully settled is more likely to be discharged with the water flow; at the same time, the high-speed overflow may cause an air vortex, and the bubbles carrying sediment will spread with the wake, exacerbating the turbidity of the water. On the contrary, if the overflow cylinder is too small, the decrease in the overflow speed will cause the overflow layer to thicken, and when the ship is sailing or shaken by the wind and waves, the slurry is likely to overflow from the top of the hopper to the deck, threatening the operation safety and restricting the loading capacity. Therefore, the reasonable design of the overflow cylinder needs to balance the overflow efficiency, sediment retention rate and safety.

[0005] Currently, there is no standardized standard for the design of overflow cylinders in the dredging construction field, and there are still significant bottlenecks in the dynamic prediction technology of the overflow layer thickness. For example, CN115114809A discloses a method and system for calculating the loss of overflow construction during loading, which builds a tidal current model, calculates the overflow sediment concentration, and then builds an overflow sediment movement model to perform overflow simulation and loss calculation. CN118519376A discloses a method, device and electronic device for controlling the overflow of a trailing suction hopper dredger, which controls the descent and ascent of the overflow cylinder by obtaining the real-time image of the overflow cylinder and using the RGB difference of the image, so as to shorten the overflow time. Most of the existing technologies focus on the offline simulation of static working conditions, calculate or evaluate the macroscopic process of the overflow process, and it is difficult to provide an optimization reference for the control of the overflow process and the design of the overflow cylinder size.

[0006] Therefore, there is an urgent need to establish a dynamic prediction method for the overflow state and provide a reference for the reasonable design of the overflow cylinder to improve the economy and environmental friendliness of the dredging project. Summary of the Invention

[0007] The purpose of the present invention is to provide a method, device and electronic equipment for predicting the overflow state of an overflow cylinder, which can dynamically predict the overflow state of the overflow cylinder based on the numerical simulation of fluid mechanics and provide guidance for the design and optimization of the overflow cylinder.

[0008] To achieve the object of the present invention, the following technical solutions are adopted:

[0009] In the first aspect, the present invention provides a method for predicting the overflow state of an overflow cylinder, and the prediction method includes the following steps:

[0010] S101: Establish a three-dimensional model of the fluid in the hopper with an overflow cylinder;

[0011] S102: Divide the fluid domain calculation grid for the three-dimensional model to obtain a fluid domain grid model;

[0012] S103: Establish a numerical calculation model of the hopper fluid to perform a flow field calculation on the fluid domain grid model to obtain a flow field calculation result;

[0013] S104: Extract the overflow state parameters of the overflow cylinder according to the flow field calculation result and evaluate the overflow state.

[0014] The prediction method provided by the present invention uses the numerical simulation method of fluid mechanics to predict the overflow state during the loading process of the hopper of a trailing suction hopper dredger, obtain the overflow state parameters, can provide a quantitative index for the evaluation of the overflow state, and provide guidance for the optimization of the size of the overflow cylinder, solves the engineering problem of the lack of quantitative indexes for the evaluation of the overflow effect, can effectively improve the loading efficiency of the trailing suction hopper dredger, and improve the benefit of the dredging project.

[0015] Preferably, the establishment of the three-dimensional model of the fluid in the hopper with an overflow cylinder includes:

[0016] Draw a three-dimensional model of the hopper according to the shape of the hopper, set an overflow cylinder in the three-dimensional model of the hopper, draw a three-dimensional model of the overflow cylinder, and divide a surface block on one side surface of the three-dimensional model of the hopper as the inlet to obtain a three-dimensional model of the fluid in the hopper.

[0017] Preferably, the division of the fluid domain calculation grid includes:

[0018] Divide the main grid for the three-dimensional model of the fluid in the hopper;

[0019] Perform grid encryption on the wall surface area of the overflow cylinder to obtain an encrypted grid;

[0020] Divide at least 5 boundary layers on the wall surface area of the overflow cylinder.

[0021] Preferably, the size of the main body grid is 10-15% of the diameter of the overflow cylinder. For example, it can be 10%, 11%, 12%, 13%, 14% or 15%, but is not limited to the listed values. Other unlisted values within the numerical range are equally applicable.

[0022] Preferably, the size of the encrypted grid is 3-5% of the diameter of the overflow cylinder. For example, it can be 3%, 3.5%, 4%, 4.5% or 5%, but is not limited to the listed values. Other unlisted values within the numerical range are equally applicable.

[0023] In the present invention, the interlayer growth rate of the boundary layer is 1.2.

[0024] Preferably, the numerical calculation model for establishing the fluid in the sludge hold adopts ANSYS CFX.

[0025] Preferably, the numerical calculation model for establishing the fluid in the sludge hold includes:

[0026] Set the fluid model using the multiphase homogeneous model;

[0027] Set the phase boundary interaction model according to the fluid characteristics;

[0028] Solve the flow field using the standard k-ε turbulence model.

[0029] Preferably, the setting of the phase boundary interaction model according to the fluid characteristics includes:

[0030] According to the D50 particle size of the sediment in the sludge hold fluid, the fluid is divided into easily precipitating soil and difficult-to-precipitate soil;

[0031] If it is easily precipitating soil, it is set as a gas-liquid two-phase fluid, and a free surface model based on the VOF method is adopted for the gas-liquid two phases;

[0032] If it is difficult-to-precipitate soil, it is set as a gas-liquid-solid three-phase fluid, a free surface model based on the VOF method is adopted for the gas-liquid two phases, and a particle model based on the Euler-Euler method is adopted for the liquid-solid two phases.

[0033] In the present invention, when the D50 particle size of the sediment in the sludge hold fluid ≥ 0.5 mm, it is set as easily precipitating soil; when the D50 particle size of the sediment in the sludge hold fluid < 0.5 mm, it is set as difficult-to-precipitate soil.

[0034] Preferably, the parameters of the free surface model include: both the gas and liquid phases are set as continuous fluids, the velocity difference between the two phases is ignored, and based on the air density, the buoyancy effect of the liquid phase on the gas phase is reflected through the density difference between the two phases;

[0035] The parameters of the particle model include: the solid phase is set as a pseudo-continuous fluid composed of dispersed particles, the velocity difference between the two phases is considered, and the drag force model applies the Gidspow model.

[0036] Preferably, the flow field calculation includes setting boundary conditions.

[0037] The boundary conditions include: setting the upper surface of the mud tank as an open surface; setting the inlet of the mud tank as a flow inlet; setting the outlet of the overflow cylinder as a pressure outlet.

[0038] Preferably, the overflow state parameters include:

[0039] At least one of the height of the overflow surface, the thickness of the overflow layer, the distance between the overflow surface and the top of the mud tank, the sediment volume fraction at the outlet of the overflow cylinder, or the air volume fraction at the outlet of the overflow cylinder.

[0040] Preferably, calculating the overflow state parameters of the overflow cylinder includes:

[0041] Selecting the flow field calculation results;

[0042] According to the selected flow field calculation results, respectively extracting the data of the sediment volume fraction at the outlet of the overflow cylinder and / or the air volume fraction at the outlet of the overflow cylinder;

[0043] In each of the selected flow field calculation results, inserting an isosurface of the gas volume fraction, the isosurface of the gas volume fraction intersects with the wall of the mud tank to form an intersection line, extracting the average height value of the intersection line to obtain the data of the height value of the overflow surface, and calculating the data of the thickness of the overflow layer and / or the distance between the overflow surface and the top of the mud tank according to the data of the height value of the overflow surface;

[0044] Performing time-averaging processing on the extracted data to obtain the overflow state parameters.

[0045] In the present invention, the isosurface of the gas volume fraction is set according to the gas volume fraction of 10%.

[0046] Preferably, the evaluation of the overflow state includes:

[0047] Obtaining the critical distance between the overflow surface and the top of the mud tank and the critical sediment volume fraction at the outlet of the overflow cylinder;

[0048] When the sediment volume fraction at the outlet of the overflow cylinder < the critical sediment volume fraction at the outlet of the overflow cylinder, the distance between the overflow surface and the top of the mud tank > the critical distance between the overflow surface and the top of the mud tank, and the air volume fraction at the outlet of the overflow cylinder > 0, it is evaluated as a recommended overflow state;

[0049] When the sediment volume fraction at the outlet of the overflow cylinder ≥ the critical sediment volume fraction at the outlet of the overflow cylinder, it is evaluated that the overflow is too fast and the overflow loss is large;

[0050] When the distance between the overflow surface and the top of the mud tank ≤ the critical distance between the overflow surface and the top of the mud tank, it is evaluated that the fluid in the mud tank overflows.

[0051] When the air volume fraction at the outlet of the overflow cylinder is 0, it is evaluated that the pipe in the cylinder is full of fluid, the overflow is too slow, and there is a risk of fluid overflow.

[0052] Preferably, the prediction method further includes: optimizing the size of the overflow cylinder according to the evaluation of the overflow state.

[0053] Preferably, optimizing the size of the overflow cylinder includes:

[0054] When the evaluation of the overflow state is that the overflow is too fast and / or the overflow loss is large, the diameter of the overflow cylinder is reduced;

[0055] When the evaluation of the overflow state is that the overflow is too slow and / or there is a risk of fluid overflow, the diameter of the overflow cylinder is increased;

[0056] After the diameter of the overflow cylinder is adjusted, the evaluation of the overflow state is repeated until the recommended overflow state is reached.

[0057] In a second aspect, the present invention provides a prediction device for the overflow state of an overflow cylinder, and the prediction device includes:

[0058] A three-dimensional model module for drawing and establishing a three-dimensional model of the fluid in the mud tank provided with an overflow cylinder;

[0059] A mesh generation module for generating computational grids for the fluid domain of the three-dimensional model;

[0060] A flow field calculation module for establishing a numerical calculation model and performing flow field calculations;

[0061] An overflow state evaluation module for obtaining overflow state parameters according to the flow field calculation results and evaluating the overflow state.

[0062] In a third aspect, the present invention provides an electronic device, and the electronic device includes:

[0063] At least one processor; and

[0064] A memory communicatively connected to the at least one processor; wherein,

[0065] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the prediction method for the overflow state of the overflow cylinder according to the first aspect.

[0066] Compared with the prior art, the present invention has the following beneficial effects:

[0067] The prediction method provided by the present invention uses a numerical simulation method of fluid mechanics to predict the overflow state during the loading process of the hopper of a trailing suction hopper dredger, obtain the overflow state parameters, which can provide a quantitative index for the evaluation of the overflow state and guidance for the optimization of the overflow pipe size, solve the engineering problem of the lack of quantitative indexes for the evaluation of the overflow effect, effectively improve the loading efficiency of the trailing suction hopper dredger, and enhance the benefit of the dredging project. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 is a flowchart of the prediction method for the overflow state of the overflow pipe provided in Embodiment 1;

[0069] Figure 2 is a schematic diagram of the three-dimensional model of the fluid in the hopper provided in Embodiment 1;

[0070] Among them, 1, inlet of the hopper; 2, upper surface of the hopper; 3, overflow pipe; 4, inlet of the overflow pipe; 5, outlet of the overflow pipe;

[0071] Figure 3 is a schematic diagram of the overflow state parameters provided in Embodiment 1;

[0072] Figure 4 is a schematic diagram of the prediction device for the overflow state of the overflow pipe provided in Embodiment 3;

[0073] Figure 5 is a schematic diagram of the structure of the electronic device for implementing the prediction method provided in Embodiment 4. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0074] The technical solutions of the present invention will be further described below through specific embodiments. Those skilled in the art should understand that the embodiments are only for helping to understand the present invention and should not be regarded as specific limitations on the present invention.

[0075] Embodiment 1

[0076] This embodiment provides a prediction method for the overflow state of the overflow pipe as shown in Figure 1 Based on the fluid dynamics software Ansys CFX, the prediction method includes:

[0077] S101: Establish a three-dimensional model of the fluid in the hopper with an overflow pipe;

[0078] S102: Divide the fluid domain calculation grid for the three-dimensional model to obtain a fluid domain grid model;

[0079] S103: Establish a numerical calculation model of the fluid in the hopper to perform a flow field calculation on the fluid domain grid model to obtain a flow field calculation result;

[0080] S104: Extract the overflow state parameters of the overflow pipe according to the flow field calculation result to evaluate the overflow state.

[0081] The specific steps are as follows:

[0082] (1) Establish a three-dimensional model of the fluid in the sludge tank equipped with an overflow cylinder.

[0083] Draw a three-dimensional model of the sludge tank according to the shape and size of the sludge tank. There is an inlet on one end face of the sludge tank. Divide a rectangular surface block at the corresponding position on one end face of the three-dimensional model of the sludge tank as the inlet.

[0084] An overflow cylinder is arranged in the sludge tank. Establish a three-dimensional model of the overflow cylinder in the sludge tank. The shape of the overflow cylinder is a cylinder. In the modeling, the wall thickness of the overflow cylinder is ignored, and the wall surface of the overflow cylinder is characterized by a curved surface to obtain a three-dimensional model of the fluid in the sludge tank, as Figure 2 shown.

[0085] (2) Divide the fluid domain calculation grid for the three-dimensional model.

[0086] Perform the main grid division on the three-dimensional model of the fluid in the sludge tank according to the size of the grid unit at 10 - 15% of the diameter D of the overflow cylinder.

[0087] Perform grid encryption on the wall surface area of the overflow cylinder to obtain an encrypted grid. The size of the encrypted grid unit is 3 - 5% of the diameter D of the overflow cylinder.

[0088] Divide at least 5 boundary layers at the wall surface of the overflow cylinder, and the growth rate between layers is 1.2.

[0089] (3) Establish a numerical calculation model for the fluid state of the fluid in the sludge tank.

[0090] (3.1) The fluid model adopts the free surface model of multiphase flow homogeneous.

[0091] Select the free surface model of the multiphase homogeneous model provided by CFX (Multiphase Homogeneous Model).

[0092] The free surface model is based on the VOF method to track the interface between multiple fluids, and its core is to track the phase interface through the volume fraction equation.

[0093] The VOF method introduces a volume fraction function for each phase of fluid. In each control unit, the sum of the volume fractions of all phases is 1, that is:

[0094]

[0095] For the q-th phase of fluid, the volume fraction continuity equation is:

[0096]

[0097] In the formula, α q is the volume fraction of the q-th phase fluid in the unit; t is the time; v is the velocity component; ρ is the density of the fluid; is the gradient operator.

[0098] The property parameters of the phases can all be expressed by the weighted values of the volume fractions. For example, density.

[0099] The density of the mixed fluid can be expressed as:

[0100]

[0101] In the formula, ρ is the density of the fluid; α q is the volume fraction of the q-th phase fluid in the unit; ρ q is the density of the q-th phase fluid.

[0102] The momentum equation is:

[0103]

[0104] In the formula, P is the pressure; v is the velocity component; ρ is the density of the fluid; μ is the fluid viscosity; F surface is the surface tension source phase; F gravity is the gravity source term.

[0105] (3.2) Set the calculation model of the phase boundary action according to the fluid characteristics.

[0106] The fluid in the mud tank is divided into easily precipitated soil and difficultly precipitated soil according to the D50 particle size of the sediment in the mud tank fluid.

[0107] When the sediment D50 particle size ≥ 0.5 mm, it is set as easily precipitated soil; when the sediment D50 particle size < 0.5 mm, it is set as difficultly precipitated soil.

[0108] (3.2.1) For easily precipitated soil, it is set as a gas-liquid two-phase fluid.

[0109] The fluid pair is set as the gas phase and the liquid phase. The free surface model provided by CFX is selected between the gas phase and the liquid phase.

[0110] Both the gas phase and the liquid phase are set as continuous fluids.

[0111] Ignore the velocity difference between the two phases, and do not consider the relative motion between the gas phase and the liquid phase during the solution.

[0112] Based on the air density, the buoyancy effect of the liquid phase on the gas phase is reflected through the density difference between the two phases. Specifically, in the free surface model, the gravity source term is expressed as:

[0113]

[0114] In the formula, ρ l is the density of the liquid phase; ρ g is the density of the gas phase; V is the volume; g is the acceleration due to gravity.

[0115] (3.2.2) For soils that are difficult to precipitate, it is set as a gas-liquid-solid three-phase fluid.

[0116] The gas-liquid two-phase is set as a continuous fluid, and the solid phase is set as a pseudo-continuous fluid composed of dispersed particles.

[0117] For the fluid pair of gas phase and liquid phase, the free surface model provided by CFX is selected between the gas-liquid phases. The velocity difference between the two phases is ignored in the calculation, and based on the air density, the buoyancy effect of the liquid phase on the gas phase is reflected through the density difference between the two phases.

[0118] For the fluid pair of solid phase and liquid phase, the particle model provided by CFX is selected between the solid-liquid phases. The velocity difference between the two phases is considered in the calculation, and the drag force model applies the Gidspow model.

[0119] The particle model is based on the Euler-Euler method.

[0120] The continuity equation of the particle phase is expressed as:

[0121]

[0122] In the formula, α k is the volume fraction; ρ k is the density; v k is the velocity component; S k is the mass source term.

[0123] The momentum equation of the particle phase is expressed as:

[0124]

[0125] In the formula, α k is the volume fraction; ρ k is the density; v k is the velocity component; P is the pressure; τ k is the particle tensor; M k is the inter-phase momentum exchange term.

[0126] M k includes the drag force, and the drag force model applies the Gidspow model.

[0127] The Gidspow model includes the Wen-Yu model and the piecewise formula of the Wen-Yu model.

[0128] The expression of the Gidspow model is as follows:

[0129]

[0130] In the formula, α s is the volume fraction of the solid phase; α l is the volume fraction of the liquid phase; ρ l is the density of the liquid phase; d s is the particle diameter of the solid phase; v l , v s are the velocity components of the liquid phase and the solid phase respectively; μ l is the dynamic viscosity of the liquid phase; C D is the drag coefficient of the Wen-Yu model.

[0131] The expression of the drag coefficient C D is as follows:

[0132]

[0133] Among them, the particle Reynolds number Re s is defined as:

[0134]

[0135] The Wen-Yu model corrects the drag force through α l -2.65 to reflect the weakening of the interaction between particles at low concentrations.

[0136] (3.3) Apply the standard k-ε turbulence model to solve the flow field.

[0137] The basic equations of the standard k-ε turbulence model are:

[0138] The expression of the turbulent kinetic energy k equation is as follows:

[0139]

[0140] The expression of the turbulent dissipation rate ε equation is as follows:

[0141]

[0142] Among them, ρ is the density; σ k , σ ε are the turbulent Prandtl numbers of k and ε respectively; μ is the dynamic viscosity coefficient of the fluid molecules; μ t is the turbulent viscosity coefficient; x i , x j are the coordinate components respectively; ui is the velocity component; C 1ε , C 2ε are model constants respectively.

[0143] G is the turbulent kinetic energy generation term caused by the average velocity gradient, and the expression is:

[0144]

[0145] where, u i , u j are velocity components.

[0146] μ t is the turbulent viscosity coefficient, which can be obtained from the turbulent kinetic energy k and the turbulent dissipation rate ε, and the expression is:

[0147]

[0148] In the standard k-ε model, C 1ε = 1.44, C 2ε = 1.92, C μ = 0.09, σ k = 1.0, σ ε = 1.3.

[0149] Take the calculation residual lower than 10 -4 as the numerical calculation convergence criterion.

[0150] (4) Set the boundary conditions, conduct the flow field calculation, and obtain the flow field calculation results.

[0151] Set the upper surface of the three-dimensional model of the mud hold fluid as the open surface, and the initial parameters include: the gas volume fraction is 100%, the pressure is the standard atmospheric pressure P atm , and the flow velocity is 0.

[0152] Set the inlet hatch as the flow inlet. For the easily sedimented soil, the flow value is set according to the mortar flow value under the inlet condition, and the initial liquid phase volume fraction is 100%; for the difficult-to-sediment soil, the flow value is set according to the mortar flow value under the inlet condition, and the initial solid phase volume fraction is set according to the loading sediment volume concentration under the design condition, and the sum of the liquid phase volume fraction and the solid phase volume fraction is 1.

[0153] Set the outlet of the overflow cylinder as the pressure outlet and set the static pressure condition. The initial pressure value is the sum of the converted pressure (ρgh d ) corresponding to the full-load draft depth h d of the mud hold and the atmospheric pressure (P atm ), that is, ρgh d + P atm .

[0154] The flow field calculation uses 1 s as the time step.

[0155] (5) Process the computational results of the flow field to obtain the overflow state parameters, such as Figure 3 shown

[0156] Select the 10s data after the flow field state stabilizes

[0157] During the calculation process, monitor the mass flow rate at the outlet of the overflow cylinder, and use the change rate of the fluctuation amplitude of the outlet mass flow rate value as the judgment index. When the change rate is less than 10%, the flow field state reaches stability

[0158] Insert the isosurfaces with a gas volume fraction of 10% into the computational results of the flow field per second

[0159] In the flow field results of any second, the isosurface intersects the surrounding walls of the sludge tank model. Extract the height value between the intersecting line and the bottom surface of the sludge tank, calculate the average value, and obtain the height of the overflow surface at this moment, denoted as Z i .

[0160] Take the difference between the height of the overflow surface and the height of the overflow cylinder (Z0), that is, Z i - Z0, to obtain the thickness of the overflow layer at this moment, denoted as Δz i .

[0161] Take the difference between the height of the upper surface of the sludge tank and the height of the overflow surface to obtain the distance between the overflow surface and the upper surface of the sludge tank at this moment, denoted as L i .

[0162] The solid volume fraction at the outlet of the overflow cylinder at this moment, denoted as α s,i .

[0163] The gas volume fraction at the outlet of the overflow cylinder at this moment, denoted as α g,i .

[0164] Perform time averaging on the numerical values of the selected 10s data respectively to obtain the corresponding time average values as the final results, which are: the height Z of the overflow surface, the thickness Δz of the overflow layer, the distance L between the overflow surface and the upper surface of the sludge tank, the sediment volume fraction α at the outlet of the overflow cylinder s , the air volume fraction α at the outlet of the overflow cylinder g .

[0165] (6) Use L, α s , α g as the overflow effect evaluation indicators to guide the optimization of the overflow cylinder size

[0166] α0 is the sediment volume fraction at the outlet of the critical overflow cylinder used by the trailing suction hopper dredger, which is proposed by the ship user

[0167] $H_0$ is the distance between the critical overflow surface used by the trailing suction hopper dredger and the upper surface of the hopper, which is set according to the hopper size, the ship's rolling characteristics, and the hydrological conditions of the designed construction water area.

[0168] When $\alpha$ s $<\alpha_0$, during the loading process, keep $L > H_0$, and $\alpha$ g is close to 0, then it is the recommended overflow state.

[0169] When $\alpha$ s $\geq\alpha_0$, there will be too fast overflow, resulting in insufficient sediment settlement in the hopper and excessive overflow loss. It is necessary to reduce the diameter $D$ of the overflow pipe.

[0170] When $L\leq H_0$, there will be overflow of the hopper fluid during the construction process, and it is necessary to increase the diameter $D$ of the overflow pipe.

[0171] When $\alpha$ g $= 0$, the flow in the overflow pipe is in a full-pipe state, and there may be too slow overflow and the continuous increase of the overflow layer thickness, with the risk of hopper fluid overflow. It is necessary to appropriately increase the diameter $D$ of the overflow pipe.

[0172] After adjusting the diameter of the overflow pipe, re-evaluate the overflow state of the hopper according to steps (1) to (5) until it is in the recommended overflow state.

[0173] Embodiment 2

[0174] This embodiment provides a prediction method for the overflow state of the overflow pipe, and applies the prediction method provided in Embodiment 1 to illustrate the technical solution of the present invention with a specific calculation process.

[0175] The steps of the prediction method are as follows:

[0176] (1) Establish a three-dimensional model of the hopper fluid with an overflow pipe.

[0177] Draw the three-dimensional model of the hopper fluid and the overflow pipe.

[0178] (2) Divide the calculation grid for the three-dimensional model.

[0179] The diameter $D$ of the overflow pipe is 1500 mm.

[0180] Divide the main grid for the hopper fluid, and the size of the main grid is set to 150 mm, which is 10% of the diameter $D$ of the pipe.

[0181] For the grid within a distance of 3000 mm along the wall surface area of the overflow pipe, the grid is encrypted, and the size of the encrypted grid is 60 mm, which is 4% of the diameter $D$ of the pipe.

[0182] Five boundary layers are divided at the wall surface of the overflow pipe, and the transition is carried out according to the interlayer growth rate of 1.2.

[0183] (3)Establish a calculation model for the fluid state of the sludge hold fluid.

[0184] (3.1)Select the Free Surface Model of the Multiphase Homogeneous Model provided by CFX.

[0185] (3.2)Set the phase boundary interaction model.

[0186] In this embodiment, the D50 particle size of the sediment is 0.08 mm, which belongs to the soil type with difficult sedimentation. Therefore, it is set as a three-phase fluid of gas, liquid and solid.

[0187] The gas-liquid two-phase is set as a continuous fluid, and the solid phase is set as a pseudo-continuous fluid composed of dispersed particles.

[0188] For the fluid pair of gas phase and liquid phase, select the FreeSurface model provided by CFX. The velocity difference between the two phases is ignored in the calculation. Based on the air density, the buoyancy effect of the liquid phase on the gas phase is reflected by the density difference between the two phases.

[0189] For the fluid pair of solid phase and liquid phase, select the ParticleModel provided by CFX. The velocity difference between the two phases is considered in the calculation, and the Gidspow model is applied for the drag force model.

[0190] (3.3)Apply the standard k-ε turbulence model to solve the flow field.

[0191] Take the calculation residual lower than 10 -4 as the numerical calculation convergence criterion.

[0192] (4)Set the boundary conditions, perform the flow field calculation, and obtain the flow field calculation results.

[0193] Set the upper surface of the sludge hold fluid model as an open surface. The initial parameters include: the gas volume fraction is 100%, the pressure is the standard atmospheric pressure P atm , and the flow velocity is 0.

[0194] Set the inlet hatch as a flow inlet. The flow value is set according to the mortar flow value of the inlet condition, which is 3 m 3 / s. The initial solid phase volume fraction is set according to the sediment volume concentration of the loading condition of the design condition, which is 20%. The sum of the liquid phase volume fraction and the solid phase volume fraction is 1, that is, the liquid phase volume fraction is 80%.

[0195] Set the overflow cylinder outlet as a pressure outlet and set the static pressure condition. The initial pressure value is calculated according to the full-load draft depth h d of the sludge hold (ρghd ), plus the atmospheric pressure (P atm ), that is, ρgh d +P atm . h d is 8.5 m, and the pressure value is 83385 + P atm Pa.

[0196] The flow field calculation uses 1 s as the time step.

[0197] (5) Process the flow field calculation results to obtain the overflow state parameters. After the flow field state stabilizes, that is, select the 10 s data after the mass flow rate change rate at the overflow cylinder outlet is lower than 10%.

[0198] In the flow field calculation results per second, insert the isosurface with a gas volume fraction of 10% respectively.

[0199] Perform time averaging processing on the numerical values of the selected 10 s data respectively.

[0200] The obtained overflow state parameters include:

[0201] The height Z of the overflow surface is 8.65 m; the thickness Δz of the overflow layer is 0.65 m; the distance L between the overflow surface and the upper surface of the mud tank is 2.05 m; the sediment volume fraction α s at the overflow cylinder outlet is 8%; the air volume fraction α g at the overflow cylinder outlet is 0.65%.

[0202] (6) Use L, α s , α g as the overflow effect evaluation indicators to guide the optimization of the overflow cylinder size.

[0203] The critical sediment volume fraction α0 at the overflow cylinder outlet is 6%.

[0204] α s = 8% ≥ 6%, breaking through the critical state, the overflow is too fast, resulting in the sediment in the loading tank not being fully precipitated, and the overflow loss is too large. It is necessary to reduce the diameter D of the overflow cylinder.

[0205] The distance H0 between the upper surface of the critical overflow layer and the upper surface of the mud tank is 1.5 m.

[0206] L = 2.05 m > 1.5 m, not breaking through the critical state.

[0207] α g is 0.65%, not equal to 0, not reaching the critical state.

[0208] Therefore, the optimization conclusion is to reduce the diameter D of the overflow cylinder.

[0209] After reducing the diameter of the overflow cylinder, recalculate the overflow state according to steps (1) to (5) until the recommended overflow state is reached.

[0210] After iteration, the optimized cylinder diameter D of the overflow cylinder is 1300 mm, Z = 8.47 m, Δz = 0.47 m, L = 2.23 m, α s = 4%, α g = 0.5%, and it is in the recommended overflow state.

[0211] Embodiment 3

[0212] This embodiment provides a prediction device for the overflow state of an overflow cylinder, as Figure 4 shown, the prediction device includes:

[0213] A three-dimensional model module 110, a mesh generation module 120, a flow field calculation module 130, and an overflow state evaluation module 140. Among them:

[0214] The three-dimensional model module 110 is used to draw and establish a three-dimensional model of the fluid in the mud tank equipped with an overflow cylinder.

[0215] The mesh generation module 120 is used to divide the fluid domain calculation mesh for the three-dimensional model.

[0216] The flow field calculation module 130 is used to establish a numerical calculation model and perform flow field calculations.

[0217] The overflow state evaluation module 140 is used to obtain the overflow state parameters according to the flow field calculation results and evaluate the overflow state.

[0218] In the mesh generation module 120, the main mesh is divided for the mud tank fluid model, and the mesh is refined in the area of the overflow cylinder wall surface.

[0219] In the flow field calculation module 130, a numerical calculation model is established and flow field calculations are performed, including:

[0220] A fluid model is established using a multiphase homogeneous model.

[0221] Set the phase boundary interaction calculation model according to the fluid characteristics, and divide the mud tank fluid into easily precipitated soil and difficult-to-precipitate soil according to the average sediment particle size of the mud tank fluid. For easily precipitated soil, it is set as a gas-liquid two-phase fluid and a free surface model is used. For difficult-to-precipitate soil, it is set as a gas-liquid-solid three-phase fluid, a free surface model is used between gas and liquid, a particle model is used between liquid and solid, and the Gidspow model is applied for the drag force model.

[0222] The turbulence model uses the standard k-ε turbulence model.

[0223] Set the boundary conditions and run the flow field calculation.

[0224] In the overflow state evaluation module 140, overflow state parameters are obtained, including: in the flow field calculation results, the solid volume fraction at the outlet of the overflow cylinder and the gas volume fraction at the outlet of the overflow cylinder are extracted, an isosurface of the gas volume fraction is inserted, the height of the overflow surface, the thickness of the overflow layer, and the distance between the overflow surface and the upper surface of the mud tank are extracted, and the extraction results are time-averaged. The finally obtained overflow parameters include: the height Z of the overflow surface, the thickness Δz of the overflow layer, the distance L between the overflow surface and the upper surface of the mud tank, and the sediment volume fraction α at the outlet of the overflow cylinder s , and the air volume fraction α at the outlet of the overflow cylinder g .

[0225] According to the overflow state parameters and the critical conditions for overflow state evaluation, the overflow state evaluation result is output.

[0226] The device provided in this embodiment can execute the prediction method for the overflow state of the overflow cylinder provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0227] Embodiment 4

[0228] This embodiment provides an electronic device for implementing the prediction method of the overflow state of the overflow cylinder, as Figure 5 shown. This electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. This electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described herein and / or claimed.

[0229] As Figure 5 shown, the electronic device 10 includes at least one processor 11 and a memory communicatively connected to at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. Among them, the memory stores a computer program executable by at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0230] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a secondary storage area, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0231] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the method for predicting the overflow state of the overflow cylinder.

[0232] In some embodiments, the method for predicting the overflow state of the overflow cylinder can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for diagnosing faults in the generator evaporation cooling system described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the method for predicting the overflow state of the overflow cylinder by any other suitable means (e.g., by means of firmware).

[0233] The various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0234] A computer program for implementing the method of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable target determination devices, such that when the computer programs are executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer programs can be executed entirely on the machine, partially on the machine, executed partially on the machine as an independent software package and partially on a remote machine, or executed entirely on a remote machine or server.

[0235] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include electrical connections based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0236] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0237] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected with each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0238] The computing system can include a client and a server. The client and the server are generally far from each other and typically interact through a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0239] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in this application can be executed in parallel, sequentially, or in a different order, as long as the information desired by the technical solution of this application can be achieved. There is no limitation herein.

[0240] The applicant declares that the above description is only a specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by any person skilled in the art within the technical scope disclosed by the present invention fall within the protection scope and the disclosure scope of the present invention.

Claims

1. A prediction method for the overflow state of an overflow cylinder, characterized in that, The prediction method includes the following steps: Establish a three-dimensional model of the fluid in the sludge tank equipped with an overflow cylinder; Divide the fluid domain calculation grid for the three-dimensional model to obtain a fluid domain grid model; Establish a numerical calculation model of the fluid in the sludge tank to perform a flow field calculation on the fluid domain grid model to obtain a flow field calculation result; According to the flow field calculation result, extract the overflow state parameters of the overflow cylinder and evaluate the overflow state.

2. The prediction method according to claim 1, wherein The establishment of the three-dimensional model of the fluid in the sludge tank equipped with an overflow cylinder includes: Draw a three-dimensional model of the sludge tank according to the shape of the sludge tank, set an overflow cylinder in the three-dimensional model of the sludge tank, draw a three-dimensional model of the overflow cylinder, and divide a surface block on one side surface of the three-dimensional model of the sludge tank as the inlet to obtain a three-dimensional model of the fluid in the sludge tank.

3. The prediction method according to claim 1, wherein The division of the fluid domain calculation grid includes: Divide the main grid for the three-dimensional model of the fluid in the sludge tank, and the size of the main grid is 10-15% of the diameter of the overflow cylinder; Perform grid encryption on the wall surface area of the overflow cylinder to obtain an encrypted grid, and the size of the encrypted grid is 3-5% of the diameter of the overflow cylinder; Divide at least 5 boundary layers on the wall surface area of the overflow cylinder.

4. The prediction method according to claim 1, characterized in that The ANSYS CFX is used to establish the numerical calculation model of the fluid in the sludge tank; The establishment of the numerical calculation model of the fluid in the sludge tank includes: Set the fluid model using a multiphase homogeneous model; Set the phase interface interaction model according to the fluid characteristics; Use the standard k-ε turbulence model to solve the flow field.

5. The prediction method according to claim 4, wherein The setting of the phase interface interaction model according to the fluid characteristics includes: According to the D50 particle size of the sediment in the fluid of the sludge tank, divide the fluid into easily sedimented soil and difficult-to-sediment soil; If it is easily sedimented soil, set it as a gas-liquid two-phase fluid, and use a free surface model based on the VOF method for the gas-liquid two phases; If it is difficult-to-sediment soil, set it as a gas-liquid-solid three-phase fluid, use a free surface model based on the VOF method for the gas-liquid two phases, and use a particle model based on the Euler-Euler method for the liquid-solid two phases; The parameters of the free surface model include: both the gas and liquid phases are set as continuous fluids, the velocity difference between the two phases is ignored, and based on the air density, the buoyancy effect of the liquid phase on the gas phase is reflected by the density difference between the two phases; The parameters of the particle model include: the solid phase is set as a pseudo-continuous fluid composed of dispersed particles, the velocity difference between the two phases is considered, and the Gidspow model is applied for the drag force model.

6. The prediction method according to claim 1, wherein The overflow state parameters include: At least one of the height of the overflow surface, the thickness of the overflow layer, the distance between the overflow surface and the top of the sludge tank, the sediment volume fraction at the outlet of the overflow cylinder, or the air volume fraction at the outlet of the overflow cylinder; The calculation of the overflow state parameters of the overflow cylinder includes: Select the flow field calculation result; According to the selected flow field calculation result, respectively extract the data of the sediment volume fraction and / or the air volume fraction at the outlet of the overflow cylinder; In each of the selected flow field calculation results, insert an isosurface of the gas volume fraction, the isosurface of the gas volume fraction intersects with the wall surface of the sludge tank to form an intersection line, extract the average height value of the intersection line to obtain the data of the height value of the overflow surface, and calculate the data of the thickness of the overflow layer and / or the distance between the overflow surface and the top of the sludge tank according to the data of the height value of the overflow surface; The extracted data is time-averaged to obtain the overflow state parameters.

7. The prediction method according to claim 6, wherein The evaluation of the overflow state includes: Obtaining the critical distance between the overflow surface and the top of the mud tank and the critical sediment volume fraction at the outlet of the overflow cylinder; When the sediment volume fraction at the outlet of the overflow cylinder < the critical sediment volume fraction at the outlet of the overflow cylinder, the distance between the overflow surface and the top of the mud tank > the critical distance between the overflow surface and the top of the mud tank, and the air volume fraction at the outlet of the overflow cylinder > 0, it is evaluated as a recommended overflow state; When the sediment volume fraction at the outlet of the overflow cylinder ≥ the critical sediment volume fraction at the outlet of the overflow cylinder, it is evaluated that the overflow is too fast and the overflow loss is large; When the distance between the overflow surface and the top of the mud tank ≤ the critical distance between the overflow surface and the top of the mud tank, it is evaluated that the fluid in the mud tank overflows; When the air volume fraction at the outlet of the overflow cylinder is 0, it is evaluated that the pipe is full of fluid inside the cylinder, the overflow is too slow, and there is a risk of fluid overflow.

8. The prediction method according to claim 7, wherein The prediction method further includes: optimizing the size of the overflow cylinder according to the overflow state evaluation; The optimization of the size of the overflow cylinder includes: When the overflow state evaluation is that the overflow is too fast and / or the overflow loss is large, the diameter of the overflow cylinder is reduced; When the overflow state evaluation is that the overflow is too slow and / or there is a risk of fluid overflow, the diameter of the overflow cylinder is increased; After the diameter of the overflow cylinder is adjusted, the overflow state evaluation is repeated until it is in the recommended overflow state.

9. A prediction device for the overflow state of an overflow cylinder, characterized in that, The prediction device includes: A three-dimensional model module for drawing and establishing a three-dimensional model of the mud tank fluid provided with an overflow cylinder; A mesh generation module for meshing the fluid domain calculation grid of the three-dimensional model; A flow field calculation module for establishing a numerical calculation model and performing flow field calculations; An overflow state evaluation module for obtaining the overflow state parameters according to the flow field calculation results and evaluating the overflow state.

10. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the prediction method for the overflow state of the overflow cylinder according to any one of claims 1-8.

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