Deep-sea aquaculture work ship hydrodynamic numerical prediction method and device thereof

Abstract

This invention discloses a numerical prediction method and equipment for the hydrodynamics of a deep-sea aquaculture vessel, comprising: S1, establishing a numerical prediction model and meshing the hull and mesh surfaces of the aquaculture vessel; S2, determining the wave frequency, wave direction, and porosity coefficient of the metal mesh in the calculation; S3, directly solving the velocity potential at each point using the boundary element method to calculate the wave excitation force, added mass coefficient, damping coefficient, and motion response amplitude operator data of the aquaculture vessel; S4, repeating step S3 to obtain hydrodynamic calculation data under different input parameters of S2, and post-processing the calculation data results under different degrees of freedom to predict the seakeeping performance of the aquaculture vessel. This invention can significantly reduce the number of elements required for calculation, improve computational efficiency, consider the hydrodynamic coupling effect between the hull and the mesh, achieve efficient numerical prediction of the hydrodynamics and seakeeping performance of aquaculture vessels, and improve the computational efficiency of structural design and mooring system design.

Description

Technical Field

[0001] This invention relates to the technical field of marine engineering equipment, and in particular to a method and equipment for numerical prediction of hydrodynamics of deep-sea aquaculture vessels. Background Technology

[0002] With economic development, the demand for high-quality marine aquaculture products is rapidly increasing. Compared to traditional shallow-water aquaculture, deep-sea aquaculture offers advantages such as vast aquaculture space, a relatively friendly environment, high aquaculture efficiency, and superior product quality. Therefore, the development of marine aquaculture, represented by deep-sea aquaculture, is a globally recognized trend. However, the deep-sea environment is complex and unpredictable, lacking protective barriers. Traditional flexible aquaculture cages cannot withstand the heavy wind and wave loads, resulting in significant deformation in the harsh deep-sea environment. This compromises the safety of personnel and farmed organisms, forcing a transformation and upgrade of deep-sea aquaculture equipment. Consequently, the design concept of deep-sea aquaculture vessels has emerged and developed rapidly in recent years.

[0003] Deep-sea aquaculture vessels utilize a typical hull or marine engineering structure as their main framework to provide buoyancy, and employ metal mesh to cover the structural surface for water exchange. Because deep-sea aquaculture vessels require long-term in-situ operations, predicting the wave loads and hydrodynamic performance they experience is crucial for resisting extreme environmental loads during the structural design, extreme motion response, and mooring system design phases.

[0004] Research on the hydrodynamic problems of floating bodies mainly employs two methods: physical experiments and numerical simulation. Numerical simulation, due to its flexibility in avoiding model size, measurement accuracy, and non-human interference, and its lower cost, has seen rapid development in recent years with the improvement of computing power. Metal mesh structures are an important component of deep-sea aquaculture vessels, subjected to complex wave and current effects; therefore, studying their hydrodynamic performance is of great significance. Currently, numerical simulations of metal mesh structures primarily utilize two methods: the Morison model and the Screen model. Both methods are derived from drag formulas, are simple in principle, and widely applied. The Morison method treats the forces on the metal mesh as the sum of the forces on individual ropes, while the Screen method treats the metal mesh as an equivalent structure composed of multiple panels.

[0005] Considering that the radiation and diffraction generated by the large-volume hull structure of deep-sea aquaculture vessels moving in waves will cause the motion of water particles around the metal mesh to differ from that under the influence of only incident waves, the hydrodynamic load on the metal mesh will be affected by the hull. Simultaneously, the hydrodynamic effect of the metal mesh will, in turn, affect the motion response of the hull structure. However, current technology separates the hull and the metal mesh, using potential flow theory for calculations of the hull and the Morison or Screen method for the metal mesh structure. These two parts are independent of each other, failing to account for the hydrodynamic coupling between the hull and the metal mesh.

[0006] Furthermore, the Morison and Screen methods still heavily rely on experience in selecting damping coefficients. The Morison method also requires a large number of elements to represent the structure to ensure computational accuracy, which significantly limits its application on large deep-sea aquaculture vessels. Therefore, numerical prediction based on hydrodynamic values ​​calculated using existing methods has low efficiency and accuracy.

[0007] Deep-sea aquaculture vessels are affected by environmental factors such as wind, waves, and currents during operation, resulting in varying hydrodynamic and kinematic responses. Hydrodynamic performance prediction is a crucial aspect of the design, construction, and operation of deep-sea aquaculture vessels. It assesses their performance, safety, and economic viability, providing a basis for optimized design, structural strength analysis, stability analysis, maneuverability analysis, and navigation planning. Considering the large investment and harsh operating environment of deep-sea aquaculture vessels, their structural safety is paramount. Therefore, an efficient and targeted numerical calculation method is urgently needed for predicting the hydrodynamic performance of deep-sea aquaculture vessels to meet the demands of current engineering design and analysis. Summary of the Invention

[0008] To address the technical problems of low efficiency and accuracy in existing hydrodynamic numerical forecasting, the primary objective of this invention is to provide a method for hydrodynamic numerical forecasting of deep-sea aquaculture vessels.

[0009] Another object of the present invention is to provide an apparatus including the above-described numerical prediction method for the hydrodynamics of deep-sea aquaculture vessels.

[0010] Another object of the present invention is to provide a computer-readable medium including the above-described numerical prediction method for the hydrodynamics of deep-sea aquaculture vessels.

[0011] The technical problem of this invention is solved by the following technical solution:

[0012] A numerical prediction method for the hydrodynamics of deep-sea aquaculture vessels includes the following steps:

[0013] S1. Establish a numerical prediction model based on the physical characteristics of the deep-sea aquaculture vessel, and perform mesh division on the hull shell and metal mesh surface of the deep-sea aquaculture vessel.

[0014] S2. Determine the wave frequency, wave direction, and porosity coefficient of the metal mesh in the calculation;

[0015] S3. The velocity potential at each point of the deep-sea aquaculture vessel is directly solved using the boundary element method, and then the wave excitation force, added mass coefficient, damping coefficient and motion response amplitude operator data of the deep-sea aquaculture vessel are obtained by numerical calculation.

[0016] S4. Repeat step S3 for any wave frequency, wave direction, and porosity coefficient of the metal mesh to obtain hydrodynamic calculation data under different wave frequencies, wave directions, and porosity coefficients of the metal mesh. Then, post-process the calculation data results under different degrees of freedom to make numerical predictions of the wave resistance performance of deep-sea aquaculture vessels.

[0017] In some embodiments, in step S1, the physical characteristics of the deep-sea aquaculture vessel include its geometry, mass, center of gravity, moment of inertia, and hydrostatic restoring stiffness matrix.

[0018] In some embodiments, in step S1, establishing the numerical prediction model includes simulating the metal mesh portion of the deep-sea aquaculture vessel using dipole elements with a porosity effect coefficient; simulating the portions of the deep-sea aquaculture vessel on both sides that are subjected to fluid but are not permeable using dipole elements without a porosity effect coefficient; and simulating the remaining portions of the deep-sea aquaculture vessel using panel elements.

[0019] In some embodiments, in step S2, the frequency and direction of the wave are determined according to actual calculation requirements; the range of the wave direction is 0-360°; and the porosity coefficient of the metal mesh is determined by the actual porosity of the metal mesh.

[0020] In some embodiments, step S3 further includes, before performing numerical calculations, specifically inputting the physical characteristics of the numerical prediction model established in step S1 and the grid information, as well as the wave frequency, wave direction, and porosity coefficient of the metal mesh described in step S2.

[0021] In some embodiments, in step S3, the boundary element method is a boundary element method that introduces porous medium flow boundary conditions to perform calculations on deep-sea aquaculture vessels in the frequency domain.

[0022] In some embodiments, in step S3, the boundary element method for introducing porous media flow boundary conditions establishes a relationship between the flow velocity and pressure difference on both sides of the metal mesh, i.e., the following equation holds at the metal mesh:

[0023]

[0024] in: The velocity potentials of the metal mesh facing the outer sea area and the aquaculture tank are respectively; The partial derivative in the direction of n; n j Let j be the j-degree-of-freedom component of n; i be the imaginary unit; k0 be the incident wave number; for the diffraction potential, take j = 7. For radiation potentials j = 4, 5, 6, n j = (r×n) j-3 r represents the position vector of a point on the surface relative to the centroid; b is the porosity coefficient. Where τ is the porosity of the metal mesh, and its value ranges from 0 to 100%.

[0025] In some embodiments, in step S3, the velocity potential at each point of the deep-sea aquaculture vessel is determined by using information about the field point M = (x, y, z) and singular points. The solution to the Green's function is as follows:

[0026]

[0027] Wherein: the distance between the field point and the source point Distance between field point and mirror point Distance in the o-xy plane between the field point and its mirror point k is the wave number; zeroth-order Bessel function of the first kind Re represents the real part; i is the imaginary unit.

[0028] In some embodiments, in step S3, the wave excitation force experienced by the deep-sea aquaculture vessel is calculated using the following formula:

[0029]

[0030] Where i is the imaginary unit, ω is the vibration frequency, ρ is the fluid density, φ0 is the incident potential, φ7 is the diffraction potential, and n represents the unit normal vector of any point on the surface of the deep-sea aquaculture vessel.

[0031] The added mass coefficient and damping coefficient of the deep-sea aquaculture vessel are obtained according to the following formula:

[0032]

[0033] Where: φ j A represents the velocity potential of the ship's hull structure; B represents the added mass; and C represents the radiation damping. Let i and j represent the velocity potentials of the metal mesh facing outwards towards the sea and the aquaculture tank, respectively, where i and j are the traversal numbers from 1 to 6, and n is the velocity potential. iLet A and B be the i-th degree of freedom components of n, therefore both A and B are 6×6 matrices;

[0034] The motion response amplitude operator of the deep-sea aquaculture vessel is obtained according to the following formula:

[0035]

[0036] Wherein: F ex C is the wave excitation force matrix of the aquaculture vessel; A is the mass matrix; B is the additional mass matrix; and K is the radiation damping matrix.

[0037] The present invention also proposes a hydrodynamic numerical prediction device for deep-sea aquaculture vessels, comprising a processor and a memory, wherein the memory stores a computer program, which can be executed by the processor to implement the above-mentioned hydrodynamic numerical prediction method for deep-sea aquaculture vessels.

[0038] The present invention also proposes a computer-readable medium storing a computer program that can be read to implement the above-described method for numerical prediction of hydrodynamics of deep-sea aquaculture vessels.

[0039] The beneficial effects of this invention compared to the prior art include:

[0040] This invention combines potential flow theory and porous media flow theory, utilizing the boundary element method (BEM) for numerical calculations of deep-sea aquaculture vessels. Compared to the Morison method used in existing technologies, the BEM only requires discretization at the boundary rather than the entire flow domain, and the required number of structural meshes is much smaller than that of the Morison method, thus saving significant computational resources and time. Furthermore, the Morison method requires indirectly solving for the velocity potential by solving the relationship between pressure potential and velocity potential, while the BEM can directly solve for the velocity potential at each point on the deep-sea aquaculture vessel, avoiding the introduction of additional errors. Therefore, this invention can significantly reduce the number of elements required for calculation, improve computational efficiency, and, considering the hydrodynamic coupling effect between the hull and the metal mesh, achieve efficient numerical prediction of the hydrodynamics and seakeeping of deep-sea aquaculture vessels, improving the computational efficiency of structural design and mooring system design.

[0041] Other beneficial effects of the embodiments of the present invention will be further described below. Attached Figure Description

[0042] Figure 1 This is a flowchart of the deep-sea aquaculture vessel hydrodynamic numerical prediction method in an embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram of the boundary of the deep-sea aquaculture vessel in an embodiment of the present invention;

[0044] Figure 3This is a front view of the deep-sea aquaculture vessel in an embodiment of the present invention;

[0045] Figure 4 This is a top view of the deep-sea aquaculture vessel in an embodiment of the present invention;

[0046] Figure 5 This is a schematic diagram illustrating the relationship between the additional mass coefficient and frequency in the roll direction in an embodiment of the present invention;

[0047] Figure 6 This is a schematic diagram illustrating the relationship between the radiation damping coefficient and frequency in the roll direction in an embodiment of the present invention;

[0048] Figure 7 This is a schematic diagram illustrating the relationship between the wave excitation force and frequency in the roll direction in an embodiment of the present invention;

[0049] Figure 8 This is a schematic diagram showing the relationship between the roll motion response amplitude operator and frequency in an embodiment of the present invention. Detailed Implementation

[0050] The present invention will be further described below with reference to the accompanying drawings and preferred embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0051] It should be noted that the directional terms such as left, right, up, down, top, and bottom used in this embodiment are only relative concepts or are based on the normal use of the product, and should not be considered as restrictive.

[0052] The hydrodynamic interaction between the hull and the metal mesh of a deep-sea aquaculture vessel is a crucial factor in its design and performance evaluation, and it also represents a complex nonlinear problem. Considering this interaction during numerical calculations can yield more realistic hydrodynamic responses and improve the accuracy of numerical predictions.

[0053] To address the shortcomings of existing technologies that calculate the hull and metal mesh separately, failing to consider their hydrodynamic coupling, this invention proposes a numerical prediction method for the hydrodynamics of deep-sea aquaculture vessels. This method, based on potential flow theory and porous media flow theory, considers the hydrodynamic interaction between the hull and the metal mesh structure, thus reducing computational costs and improving computational efficiency. Figure 1 As shown, the steps of this method are as follows:

[0054] S1. Establish a numerical prediction model based on the physical characteristics of the deep-sea aquaculture vessel, and perform mesh division on the hull shell and metal mesh surface of the deep-sea aquaculture vessel.

[0055] The physical characteristics of deep-sea aquaculture vessels include their geometry, mass, center of gravity, moment of inertia, and hydrostatic restoring stiffness matrix.

[0056] The numerical prediction model was established by simulating the metal mesh part of the deep-sea aquaculture vessel using dipole elements with porosity effect coefficients; simulating the fluid-affected but non-porous parts on both sides of the deep-sea aquaculture vessel using dipole elements without porosity effect coefficients; and simulating the remaining parts of the deep-sea aquaculture vessel using panel elements.

[0057] S2. Determine the wave frequency, wave direction, and porosity coefficient of the metal mesh in the calculation; the wave frequency and wave direction are determined according to actual needs, with the wave direction ranging from 0 to 360°; the porosity coefficient of the metal mesh is determined by the actual porosity of the metal mesh.

[0058] S3. The velocity potential at each point of the deep-sea aquaculture vessel is directly solved using the boundary element method, and then the wave excitation force, added mass coefficient, damping coefficient and motion response amplitude operator data of the deep-sea aquaculture vessel are obtained by numerical calculation.

[0059] Specifically, before performing numerical calculations, the physical characteristics of the numerical prediction model established in step S1 and the information of the divided grid are input, as well as the wave frequency, wave direction, and porosity coefficient of the metal mesh in step S2. The boundary element method is a boundary element method that introduces porous medium flow boundary conditions to perform calculations on deep-sea aquaculture vessels in the frequency domain.

[0060] S4. Repeat step S3 for any wave frequency, wave direction, and porosity coefficient of the metal mesh to obtain hydrodynamic calculation data under different wave frequencies, wave directions, and porosity coefficients of the metal mesh. Post-process the calculation data results under different degrees of freedom, and then numerical prediction of the wave resistance performance of deep-sea aquaculture vessels can be carried out.

[0061] In this embodiment, the post-processing involves plotting the calculation results under different degrees of freedom on a two-dimensional graph with frequency as the horizontal axis for data visualization and analysis.

[0062] The working principle of the numerical prediction method for hydrodynamics of deep-sea aquaculture vessels proposed in this invention is as follows:

[0063] According to potential flow theory, when a fluid is inviscid, irrotational, and incompressible, a potential function Φ must exist. For a flow that has reached a steady state, the spatial velocity potential φ can be separated, as shown in the following equation:

[0064] Φ(x,y,z,t)=Re[φ(x,y,z)e -iωt ];

[0065] Where: x, y, z are three-dimensional spatial coordinates; t is time; ω is the vibration frequency; Re denotes taking the real part; e -iωtis the oscillation factor; i is the imaginary unit.

[0066] The first-order spatial velocity potential φ consists of the incident potential φ0, the diffraction potential φ7, and the radiation potential φ. j The expression (j = 1, 2, ..., 6) is composed of the following formula:

[0067]

[0068] Where vector M represents a flow field point with coordinates (x, y, z); ξ j The amplitude of motion corresponds to the degree of freedom; in the case of infinite water depth, the incident potential is as follows:

[0069]

[0070] Where: g is the acceleration due to gravity; A is the amplitude of the incident wave; k0 is the wave number of the incident wave, which satisfies the following in deep water. β is the wave angle.

[0071] The boundaries of deep-sea aquaculture vessels are defined as follows: Figure 2 As shown, the hull structure is represented by S, and the metal mesh portion by P. Now consider the flow region enclosed by the surface of the aquaculture vessel, its free surface, bottom surface, and a vertical cylindrical surface with an infinitely large radius R. According to potential flow theory, the diffraction potential and radiation potential φ... j (j=1,2,...,7) must satisfy the Laplace equation, free surface boundary conditions, bottom surface boundary conditions, and infinity boundary conditions within the watershed:

[0072]

[0073] And the surface boundary conditions of deep-sea aquaculture vessels:

[0074]

[0075] in, For the Laplace operator; watershed radius n represents the unit normal vector of any point on the surface of the deep-sea aquaculture vessel. The partial derivative in the direction of n; n j is the j-degree-of-freedom component of n; r represents the position vector of the object surface point relative to the centroid.

[0076] Since the thickness of the metal mesh is negligible, and the mesh size is small and uniformly distributed, in step S3, this embodiment of the invention introduces the boundary element method for porous media flow boundary conditions. Specifically, based on linear porous media flow boundary conditions, a linear relationship is established between the continuous velocity on both sides of the metal mesh and the pressure change (pressure difference), that is, the following equation holds at the metal mesh:

[0077]

[0078] in, The speed and potential of the metal mesh towards the outer sea area, The velocity potentials of the metal mesh facing the aquaculture chamber are respectively; The partial derivative in the direction of n; n j Let j be the j-degree-of-freedom component of n, r represent the position vector of the object surface point relative to the center of mass, and k0 be the incident wave number; for the diffraction potential, take j = 7. For radiation potentials j = 4, 5, 6, n j = (r×n) j-3 b is the porosity coefficient. Where τ is the porosity of the metal mesh, and its value ranges from 0 to 100%.

[0079] In step S3, the Green's function method is used to solve for each boundary condition, yielding the velocity potential function at the field points. Singular points (source points or dipole points) are selected. And its mirror point regarding the undisturbed free water surface. In the case of infinite water depth, the frequency domain Green's function for the field point and singular point is as follows:

[0080]

[0081] Among them, the distance between the field point and the source point Distance between field point and mirror point G F For free surface terms, in addition to satisfying the Laplace equation, the Green's function also satisfies the free surface boundary conditions, the object surface boundary conditions, and the boundary conditions at infinity.

[0082] Considering the presence of dipoles along the integration path, only the outward propagation wave is meaningful among the three integration paths corresponding to inward propagation, standing wave, and outward propagation, respectively. The velocity potential at each point on the deep-sea aquaculture vessel is then obtained by using the field point M = (x, y, z) and singular points. The solution for the Green's function is shown in the following equation:

[0083]

[0084] Among them, the distance between the field point and the source point Distance between field point and mirror point Distance in the o-xy plane between the field point and its mirror point k is the wave number; J0(kR') is the zeroth-order Bessel function of the first kind, expressed as: Re represents the real part; i is the imaginary unit.

[0085] After applying the Green's function, the boundary integral equations for the hull structure are as follows:

[0086]

[0087] The boundary integral equation for the metal mesh portion is shown below:

[0088]

[0089] in, and φ are the partial derivatives in the n-direction at field point M and singular point N, respectively; out (N) and φ in (N) represents the velocity potential of singular point N toward the external sea area and aquaculture tank, consisting of 7 components with subscript j that satisfy the above linear relationship between velocity and pressure.

[0090] The wave excitation force and hydrodynamic parameters experienced by the deep-sea aquaculture vessel are finally obtained as shown in the following formula:

[0091]

[0092] in: i ω is the imaginary unit, ρ is the vibration frequency, φ0 is the incident potential, φ7 is the diffraction potential, n represents the unit normal vector at any point on the surface of the deep-sea aquaculture vessel; A is the added mass; B is the radiation damping. Let i and j represent the velocity potentials of the metal mesh facing outwards towards the sea and the aquaculture tank, respectively, where i and j are the traversal numbers from 1 to 6, and n is the velocity potential. i Let A and B be the i-th degree of freedom components of n, therefore both A and B are 6×6 matrices.

[0093] The frequency domain motion equation of a deep-sea aquaculture vessel under the action of a linear regular wave is shown below:

[0094]

[0095] Where X represents the six-degree-of-freedom displacement of the deep-sea aquaculture vessel; This is the first derivative of the displacement, i.e., the six-degree-of-freedom velocity of the deep-sea aquaculture vessel; Let C be the second derivative of the displacement, i.e., the six-degree-of-freedom acceleration of the deep-sea aquaculture vessel; C is a 6×6 mass matrix; A and B are the added mass and radiation damping matrices; and K is the hydrostatic restoring stiffness matrix. Therefore, the motion response amplitude operator RAO of the deep-sea aquaculture vessel is as follows:

[0096]

[0097] Wherein: F ex C is the wave excitation force matrix of the aquaculture vessel; A is the mass matrix; B is the additional mass matrix; and K is the radiation damping matrix.

[0098] The response transfer function H is shown in the following equation:

[0099]

[0100] Wherein: F ex C is the wave excitation force matrix of the aquaculture vessel; A is the mass matrix; B is the additional mass matrix; and K is the radiation damping matrix.

[0101] Example:

[0102] S1. Establish a numerical prediction model based on the physical characteristics of the deep-sea aquaculture vessel, and perform mesh division on the hull shell and metal mesh surface of the deep-sea aquaculture vessel.

[0103] First, the surface of the deep-sea aquaculture vessel is divided into grids. The front and top views of the selected deep-sea aquaculture vessel in this embodiment are shown below. Figure 3 and Figure 4 As shown, it has a total length of 91m, a width of 19m, and a design draft of 8.8m. Inside, there is an aquaculture tank that is 45m long, 19m wide, and 7.6m high. There are 72 openings with a radius of 1m on the two side plates, which are covered with metal mesh with a porosity of 80% to facilitate the exchange of water inside and outside.

[0104] This embodiment is for example, Figure 3 The metal mesh shown in the middle grid section is simulated using dipole elements with porosity effect coefficients; the side plates, which are subjected to fluid action but are not permeable, are simulated using dipole elements without porosity effect coefficients; the remaining hull section uses panel elements. The numerical prediction model in this embodiment has a total of 1908 dipole elements with porosity effect coefficients, 1710 dipole elements without porosity effect coefficients, and 3036 panel elements. The mesh density calculated in this embodiment is sufficient for engineering accuracy requirements; for higher simulation accuracy, the mesh density can be further increased.

[0105] S2. Determine the wave frequency, wave direction, and porosity coefficient of the metal mesh in the calculation;

[0106] The wave frequency and direction to be calculated are selected. In this embodiment, the selected frequency range is 0.2 rad / s to 1.6 rad / s, with a step size of 0.025 rad / s, resulting in 57 calculation frequencies. The selected wave direction is 90°, meaning the external wave load direction is perpendicular to the line connecting the stern to the bow of the deep-sea aquaculture vessel. Under this wave direction, the deep-sea aquaculture vessel exhibits significant motion in all six degrees of freedom. The porosity coefficient of the metal mesh is selected; in this embodiment, the porosity coefficient is 172.88, corresponding to a porosity of 80% for the metal mesh.

[0107] S3. The velocity potential at each point of the deep-sea aquaculture vessel is directly solved using the boundary element method, and then the wave excitation force, added mass coefficient, damping coefficient and motion response amplitude operator data of the deep-sea aquaculture vessel are obtained through numerical calculation.

[0108] The specific process of numerical calculation in this embodiment is as follows: Figure 1 As shown, the specific inputs include the numerical prediction model grid information established in step S1, the physical information of the deep-sea aquaculture vessel such as geometry, mass, center of gravity, moment of inertia, and hydrostatic restoring stiffness matrix, additional viscous damping (if any), and wave frequency, wave direction, and metal mesh porosity coefficient.

[0109] With the above information, numerical calculations can be performed. Several singular points are arranged within the grid of the deep-sea aquaculture vessel. By solving the linear equation system, the velocity potential at each point in the flow field can be obtained. Then, by integration, the wave excitation force, added mass, and radiation damping experienced by the deep-sea aquaculture vessel can be obtained.

[0110]

[0111] Based on the mass matrix, added mass matrix, radiation damping matrix, stiffness matrix, and wave force matrix, the motion response amplitude operator of the deep-sea aquaculture vessel can be obtained:

[0112]

[0113] The calculation process ends, and the output results include the six-degree-of-freedom added mass coefficient, damping coefficient, wave excitation force, and motion response amplitude operator of the deep-sea aquaculture vessel under the input frequency, wave direction, and metal mesh porosity effect coefficient.

[0114] S4. Repeat step S3 for any wave frequency, wave direction and porosity coefficient of the metal mesh to obtain hydrodynamic calculation data under different wave frequencies, wave directions and porosity coefficients of the metal mesh, and then post-process the calculation data results under different degrees of freedom.

[0115] Step S3 was repeated for the selected frequency and wave direction, yielding a series of different calculation results. Since this calculation involved 57 frequencies, 1 wave direction, and 1 metal mesh porosity effect coefficient, a total of 1368 data points were calculated. The calculation results under different degrees of freedom were plotted on a two-dimensional graph with frequency as the horizontal axis, as shown below. Figures 5-8 As shown, where Figure 5 The results of the calculation of the additional mass coefficient in the roll direction are shown. Figure 6 The calculation results of the radiation damping coefficient in the roll direction are shown. Figure 7 The calculation results of the wave excitation force in the roll direction are shown. Figure 8 The calculation results of the roll motion response amplitude operator are shown.

[0116] The numerical prediction method for hydrodynamics of deep-sea aquaculture vessels proposed in this invention can obtain the motion response and hydrodynamic parameters of deep-sea aquaculture vessels under the action of regular waves of arbitrary frequency and wave direction, assisting in the hydrodynamic analysis of deep-sea aquaculture vessels and can be used to assist in the overall response of deep-sea aquaculture vessels and the design of mooring systems.

[0117] Correspondingly, this invention also proposes a deep-sea aquaculture vessel hydrodynamic numerical prediction device, including a processor and a memory. The memory stores a computer program, which can be executed by the processor to implement the above-mentioned deep-sea aquaculture vessel hydrodynamic numerical prediction method.

[0118] This invention also proposes a computer-readable medium storing a computer program that can be read to implement the above-described method for numerical prediction of hydrodynamics of deep-sea aquaculture vessels.

[0119] Compared with the prior art, the advantages of the embodiments of the present invention are as follows:

[0120] It is a well-known fact in the industry that the existing Morison method is computationally time-consuming and has a large mesh size. Since the existing technology uses different methods to calculate the metal mesh and the hull, it cannot take into account the mutual influence between the two.

[0121] The numerical prediction method for the hydrodynamics of deep-sea aquaculture vessels proposed in this invention draws on porous media flow theory. It applies linear porous media flow boundary conditions to the metal mesh structure and uses dipole elements to establish a numerical prediction model of the deep-sea aquaculture vessel, including both the hull and the metal mesh. Compared to existing techniques that use different methods to calculate the hull and metal mesh, this invention considers the hydrodynamic coupling relationship between the hull and the metal mesh, thus obtaining a more realistic hydrodynamic response of the deep-sea aquaculture vessel, improving the accuracy of numerical prediction, and enhancing the accuracy of subsequent structural design and parameter optimization.

[0122] This method combines potential flow theory and porous media flow theory, using the boundary element method (BEM) for numerical calculations of deep-sea aquaculture vessels. Compared to the existing Morison method, the BEM only requires discretization at the boundary, rather than the entire flow domain, and requires a significantly smaller number of structural meshes, thus saving substantial computational resources and time. Furthermore, the Morison method indirectly solves for the velocity potential by finding the relationship between pressure and velocity potentials, while the BEM directly solves for the velocity potential at each point on the deep-sea aquaculture vessel, avoiding the introduction of additional errors. Therefore, this invention significantly reduces the number of elements while minimizing errors, improving computational efficiency and solving the problems of existing numerical calculations being unable to consider hydrodynamic coupling and being time-consuming. It reduces computation time from hours to minutes, achieving efficient numerical prediction for deep-sea aquaculture vessels.

[0123] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, several equivalent substitutions or obvious modifications can be made without departing from the concept of the present invention, and all such modifications, achieving the same performance or purpose, should be considered within the scope of protection of the present invention.

Claims

1. A numerical prediction method for the hydrodynamics of deep-sea aquaculture vessels, characterized in that, Includes the following steps: S1. Establish a numerical prediction model based on the physical characteristics of the deep-sea aquaculture vessel, and perform mesh division on the hull shell and metal mesh surface of the deep-sea aquaculture vessel. S2. Determine the wave frequency, wave direction, and porosity coefficient of the metal mesh in the calculation; S3. The velocity potential at each point of the deep-sea aquaculture vessel is directly solved using the boundary element method, and then the wave excitation force, added mass coefficient, damping coefficient and motion response amplitude operator data of the deep-sea aquaculture vessel are obtained by numerical calculation. S4. Repeat step S3 for any wave frequency, wave direction and porosity coefficient of the metal mesh to obtain hydrodynamic calculation data under different wave frequencies, wave directions and porosity coefficients of the metal mesh, and post-process the calculation data results under different degrees of freedom to make numerical prediction of the wave resistance performance of deep-sea aquaculture vessels. In step S3, the boundary element method is a boundary element method that introduces porous medium flow boundary conditions, and it is used to calculate the deep-sea aquaculture vessel in the frequency domain; in the boundary element method that introduces porous medium flow boundary conditions, the relationship between the flow velocity and pressure difference on both sides of the metal mesh is established, that is, the following equation holds at the metal mesh: ； in: , The velocity potentials of the metal mesh facing the outer sea area and the aquaculture tank are respectively; for Partial derivatives in direction; for of Degrees of freedom components; The imaginary unit; Let be the incident wave number; for the diffraction potential, take . , , Let V be the incident wave velocity potential; for the radiation potential... , , The position vector of a point on the surface of an object relative to its centroid; The porosity coefficient of the metal mesh is given. ,in The porosity of the metal mesh is 0-100%.

2. The deep sea farming vessel hydrodynamic numerical prediction method of claim 1, wherein, In step S1, the physical characteristics of the deep-sea aquaculture vessel include its geometry, mass, center of gravity, moment of inertia, and hydrostatic restoring stiffness matrix. The establishment of the numerical prediction model includes simulating the metal mesh portion of the deep-sea aquaculture vessel using dipole elements with porosity effect coefficients; simulating the fluid-affected but non-porous portions on both sides of the vessel using dipole elements without porosity effect coefficients; and simulating the remaining portions of the vessel using panel elements.

3. The deep sea farming vessel hydrodynamic numerical prediction method of claim 1, wherein, In step S2, the frequency and direction of the wave are determined according to actual calculation requirements; the range of the wave direction is 0-360°; the porosity coefficient of the metal mesh is determined by the actual porosity of the metal mesh.

4. The deep sea farming vessel hydrodynamic numerical prediction method of claim 1, wherein, Step S3 also includes inputting the physical characteristics of the numerical prediction model established in step S1 and the grid information of the division, as well as the wave frequency, wave direction and porosity coefficient of the metal mesh as described in step S2, before performing numerical calculations.

5. The deep sea farming vessel hydrodynamic numerical prediction method of claim 1, wherein, In step S3, the velocity potential at each point on the deep-sea aquaculture vessel is used with respect to the field point. and singularity The solution to the Green's function is as follows: ； Wherein: the distance between the field point and the source point Distance between field point and mirror point ; o-xy plane distance between the field point and its mirror point ; Wave number; zeroth-order Bessel function of the first kind Re denotes taking the real part; It is the imaginary unit.

6. The deep sea farming vessel hydrodynamic numerical prediction method of claim 1, wherein, In step S3, the wave excitation force experienced by the deep-sea aquaculture vessel is calculated using the following formula: ； in, The imaginary unit, The vibration frequency, For fluid density, For incident potential, For diffraction, The unit normal vector representing any point on the surface of a deep-sea aquaculture vessel; The added mass coefficient and damping coefficient of the deep-sea aquaculture vessel are obtained according to the following formula: ； in: The velocity potential of the ship's hull structure; For added mass; For radiation damping; , The velocity potentials of the metal mesh facing the outer sea area and the aquaculture tank are respectively. The number of iterations from 1 to 6. for of Degrees of freedom components, therefore , All are 6×6 matrices; The motion response amplitude operator of the deep-sea aquaculture vessel is obtained according to the following formula: ； in: The wave excitation force matrix of the aquaculture vessel; This is the quality matrix; For the additional mass matrix; Here is the radiation damping matrix; This is the hydrostatic recovery stiffness matrix.

7. A deep sea farming vessel hydrodynamic numerical prediction device comprising a processor and a memory, said memory having stored therein a computer program, characterized in that, The computer program can be executed by a processor to implement the numerical prediction method for hydrodynamics of deep-sea aquaculture vessels as described in any one of claims 1-6.

8. A computer-readable medium storing a computer program, characterized in that, The computer program can be read to implement the numerical prediction method for hydrodynamics of deep-sea aquaculture vessels as described in any one of claims 1-6.

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