Net cage hydrodynamic force calculation method and system and readable storage medium

Abstract

The invention discloses a net cage hydrodynamic calculation method and system and a readable storage medium, and relates to the technical field of ocean engineering. The net cage hydrodynamic force calculation method comprises the following steps: constructing a netting porous medium CFD model, and obtaining an equivalent resistance parameter of a netting; constructing a net cage motion potential flow theoretical model, and embedding the equivalent resistance parameter into the net cage motion potential flow theoretical model to obtain a first net cage motion response; embedding into the netting porous medium CFD model according to the first net cage motion response so as to perform bidirectional dynamic coupling on the netting porous medium CFD model and the net cage motion potential flow theoretical model, and obtaining a second net cage motion response through multiple times of bidirectional dynamic coupling; and calculating the net cage hydrodynamic force according to the second net cage motion response. According to the technical scheme provided by the invention, the calculation precision of the net cage hydrodynamic force can be improved on the premise of reducing the calculation cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ocean engineering, and in particular to a net cage hydrodynamic calculation method and system and a readable storage medium. BACKGROUND

[0002] As the core aquaculture equipment in ocean engineering, the net cage has dual attributes of production platform and structure: in the nearshore and deep-sea environment, the net cage is anchored to the seabed through a mooring system and bears extreme loads such as wind, wave and current, and its motion response is directly related to the safety of aquaculture and the risk of personnel operation, so the analysis of the hydrodynamic performance of the net cage has become a key link in the design of ocean engineering.

[0003] In the prior art, the analysis of the hydrodynamic performance of the net cage mainly adopts three approaches of Morison formula, pure CFD (Computational Fluid Dynamics) and pure potential flow theory, but all have obvious limitations: first, the traditional Morison formula simplifies the net cage as an independent rod, ignoring the flow velocity attenuation and turbulent shielding effect between the multiple rows of netting of the net cage, resulting in significant calculation error of the resistance; second, although the pure CFD can capture viscous flow in detail, it faces the problem of large grid scale and high calculation cost, which is difficult to promote in engineering scale; and third, although the pure potential flow theory can quickly give the motion response of the net cage, it cannot take into account the nonlinear damping of the netting energy consumption and mooring load.

[0004] Based on the above reasons, there is an urgent need for a new type of net cage hydrodynamic calculation method that can improve the calculation accuracy of the net cage hydrodynamic performance while reducing the calculation cost.

[0005] It should be noted that the above content is only used to assist in understanding the technical solutions of the present application, and does not mean that the above content is prior art. SUMMARY

[0006] The main purpose of the present application is to provide a net cage hydrodynamic calculation method, system and readable storage medium, which aims to improve the calculation accuracy of the net cage hydrodynamic performance while reducing the calculation cost.

[0007] To achieve the above purpose, the present application provides a net cage hydrodynamic calculation method, comprising the following steps: constructing a netting porous medium CFD model to obtain equivalent resistance parameters of the netting; constructing a net cage motion potential flow theory model and embedding the equivalent resistance parameters into the net cage motion potential flow theory model to obtain a first net cage motion response; The first cage motion response is embedded into the porous medium CFD model of the mesh fabric to perform bidirectional dynamic coupling between the porous medium CFD model of the mesh fabric and the potential flow theory model of the cage motion. The second cage motion response is obtained through multiple bidirectional dynamic couplings. The hydrodynamics of the cage are calculated based on the motion response of the second cage.

[0008] In one embodiment, the step of constructing a CFD model of the porous mesh medium and obtaining the equivalent resistance parameters of the mesh includes the following steps: Construct a CFD model of the porous mesh medium; The flow state of the mesh under different inflow conditions was simulated using the porous medium CFD model of the mesh. The equivalent resistance parameter is obtained based on the flow state of the mesh.

[0009] In one embodiment, in the step of constructing the CFD model of the mesh porous medium, The CFD model of the mesh porous medium adopts a locally overlapping mesh or an immersion boundary-porous medium coupling algorithm to maintain the boundary layer analysis of y*≤1 when the mesh thickness is ≤3mm; Furthermore, the CFD model of the mesh-coated porous medium uses adaptive mesh refinement in the mesh region, and the mesh refinement trigger condition is the velocity gradient | u|≥0.2U ∞ / L_ref.

[0010] In one embodiment, the step of simulating the flow state of the mesh under different inflow conditions using the porous mesh CFD model includes simulating the different inflow conditions as follows: Steady-state flow with velocities ranging from 0.1 m / s to 2.5 m / s and intervals of 0.1 m / s; In addition, regular waves and irregular waves, with wave heights ranging from 0.5m to 6m and periods from 3s to 12s: And, oblique flow with incident angle θ = 0°~90° at intervals of 15°; The above working conditions are combined and then an offline CFD case library is generated using Latin hypercube sampling.

[0011] In one embodiment, the step of obtaining the equivalent resistance parameter based on the flow state of the mesh includes the water permeability, the resistance coefficient, and the shading effect factor.

[0012] In one embodiment, in the step of obtaining the motion response of the second cage through multiple bidirectional dynamic couplings, the convergence criteria for the bidirectional dynamic coupling are that the difference between the peak values ​​of mooring tension in two adjacent iterations is less than 5%, and the relative change of the L2 norm of the cage's center of gravity displacement is ≤3%; when both of the above criteria are met simultaneously, the iteration is terminated and the motion response of the second cage is output.

[0013] In one embodiment, the CFD model of the porous mesh medium is constructed using a CFD solver, wherein the CFD solver is OpenFOAM; and / or, the potential flow theory model of the mesh cage motion is constructed using a potential flow solver, wherein the potential flow solver is Aqwa.

[0014] In one embodiment, the CFD solver and the potential flow solver are coupled via an FMI protocol or a custom script based on Python / Bash.

[0015] To achieve the above objectives, the present invention proposes a hydrodynamic calculation system for a net cage, comprising a processor and a memory, wherein the memory stores a computer program, characterized in that the computer program can be executed by the processor to implement the hydrodynamic calculation method for the net cage as described in any of the above claims.

[0016] To achieve the above objectives, the present invention proposes a readable storage medium storing a computer program, characterized in that the computer program can be read to implement the cage hydrodynamic calculation method as described in any of the preceding claims.

[0017] The technical solution of this invention first constructs a porous medium CFD model of the netting using CFD technology to obtain its equivalent resistance parameters. Understandably, since CFD technology can accurately capture viscous flow, it avoids significant resistance calculation errors caused by neglecting velocity attenuation and turbulence shielding effects between multiple rows of netting. Then, the equivalent resistance parameters are embedded into a potential flow theory model of the net cage motion constructed using potential flow theory. Since potential flow theory can quickly provide the first net cage motion response, it helps reduce computational costs. Finally, using a two-way dynamic coupling mechanism between porous medium CFD and potential flow theory, the second net cage motion response is obtained through real-time, multiple bidirectional data exchanges between the porous medium CFD model and the potential flow theory model of the net cage motion. This breaks through the accuracy limitations of traditional unidirectional coupling and improves the computational accuracy of the net cage hydrodynamics. In other words, this application combines CFD and potential flow theory technologies, using CFD technology to calculate the local situation and potential flow theory to calculate the overall situation. The two exchange data in real-time through bidirectional dynamic coupling, iterating until convergence, thereby improving the computational accuracy of the net cage hydrodynamics while reducing computational costs. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart of one embodiment of the hydrodynamic calculation method for net cages provided by the present invention; Figure 2 The second flowchart illustrates the steps of an embodiment of the hydrodynamic calculation method for a net cage provided by the present invention.

[0020] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] The technical solutions of this invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a portion of the embodiments of this invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0022] It should be noted that if the embodiments of the present invention involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0023] Furthermore, it should be noted that the descriptions involving "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, such a combination of technical solutions should be considered non-existent and not within the scope of protection claimed by this invention.

[0024] In existing technologies, hydrodynamic analysis of gabion cages mainly employs three approaches: the Morison formula, pure CFD (Computational Fluid Dynamics), and pure potential flow theory. However, all have significant limitations: First, the traditional Morison formula simplifies the gabion cage as an independent rod, neglecting the velocity attenuation and turbulent shielding effects between multiple rows of netting, leading to significant errors in resistance calculation. Second, while pure CFD can accurately capture viscous flow, it suffers from large mesh sizes and excessively high computational costs, making it difficult to scale up for engineering applications. Third, although pure potential flow theory can quickly provide the gabion cage's motion response, it cannot account for nonlinear damping factors such as netting energy consumption and mooring loads. Therefore, a novel hydrodynamic calculation method for gabion cages is urgently needed to improve the accuracy of hydrodynamic calculations while reducing computational costs.

[0025] To address the aforementioned technical problems, this invention proposes a method for calculating the hydrodynamics of a net cage.

[0026] Please see Figure 1 In one embodiment of the present invention, the hydrodynamic calculation method for the cage includes the following steps: Step S10: Construct a CFD model of the porous mesh medium and obtain the equivalent resistance parameters of the mesh; Step S20: Construct a theoretical model of the potential flow of the cage motion, and embed the equivalent resistance parameters into the theoretical model of the potential flow of the cage motion to obtain the first cage motion response; Step S30: The first mesh cage motion response is embedded into the mesh porous medium CFD model to perform bidirectional dynamic coupling between the mesh porous medium CFD model and the mesh cage motion potential flow theoretical model. The second mesh cage motion response is obtained through multiple bidirectional dynamic couplings. Step S40: Calculate the hydrodynamic force of the cage based on the motion response of the second cage.

[0027] The technical solution of this invention first constructs a porous medium CFD model of the netting using CFD technology to obtain its equivalent resistance parameters. Understandably, since CFD technology can accurately capture viscous flow, it avoids significant resistance calculation errors caused by neglecting velocity attenuation and turbulence shielding effects between multiple rows of netting. Then, the equivalent resistance parameters are embedded into a potential flow theory model of the net cage motion constructed using potential flow theory. Since potential flow theory can quickly provide the first net cage motion response, it helps reduce computational costs. Finally, using a two-way dynamic coupling mechanism between porous medium CFD and potential flow theory, the second net cage motion response is obtained through real-time, multiple bidirectional data exchanges between the porous medium CFD model and the potential flow theory model of the net cage motion. This breaks through the accuracy limitations of traditional unidirectional coupling and improves the computational accuracy of the net cage hydrodynamics. In other words, this application combines CFD and potential flow theory technologies, using CFD technology to calculate the local situation and potential flow theory to calculate the overall situation. The two exchange data in real-time through bidirectional dynamic coupling, iterating until convergence, thereby improving the computational accuracy of the net cage hydrodynamics while reducing computational costs.

[0028] As a preferred embodiment of the above, step S10 includes the following steps: Step S11: Construct the CFD model of the porous mesh medium; In the above steps, the mesh-coated porous media CFD model employs a locally overlapping mesh or an immersion boundary-porous media coupling algorithm to maintain boundary layer resolution of y*≤1 even when the mesh thickness is ≤3mm; and the mesh-coated porous media CFD model uses adaptive mesh refinement in the mesh region, with the mesh refinement triggering condition being the velocity gradient | u|≥0.2U ∞ / L_ref.

[0029] This setup employs two distinct CFD meshing strategies: locally overlapping meshes and the immersion boundary-porous media coupling algorithm. Locally overlapping meshes (Overset / Chimera) generate a high-resolution small mesh layer in and around the mesh, which is then overlapped with the background mesh in a "building block" manner. The mesh can be as thin as 1 mm, eliminating the need for forced refinement in the global mesh and saving over 90% of the mesh size. Immersion boundary-porous media coupling treats the extremely thin mesh as a "zero-thickness" interface, adding a source term to the fluid equations using the immersion boundary method, while simultaneously providing an extremely thin porous media layer in the normal direction to dissipate the flow. This avoids generating solid thin-layer meshes while preserving the thickness effect. Through these two CFD meshing strategies, even with an extremely thin mesh (≤3 mm), much smaller than the conventional boundary layer mesh size, the dimensionless distance y* of the first mesh layer is still guaranteed to be ≤1, allowing direct analysis of the viscous sublayer. This enables high-precision wall analysis with drag coefficient errors controlled within 3%. Furthermore, the CFD solver monitors the norm of the local velocity gradient tensor in real time within the mesh region. u|. When this value reaches or exceeds the threshold 0.2U ∞ / L_ref (U ∞ (where L_ref is the inflow velocity and L is the cage characteristic scale), automatically triggering local mesh refinement. This refines the mesh in key areas such as shear layers and wakes, while maintaining a coarse mesh in other areas. This ensures solution accuracy at critical locations while significantly reducing the total mesh size; in other words, it ensures refinement only in "physically important areas," preventing the entire ocean area from becoming high-resolution, thus saving 50-70% of the mesh size. Through this technique, mesh refinement can be improved on one hand, while reducing mesh utilization on the other, lowering the hardware requirements for CFD technology, thereby further reducing computational costs while maintaining computational accuracy.

[0030] Step S12: Simulate the flow state of the mesh under different inflow conditions using the porous medium CFD model of the mesh. In the above steps, the simulation of different inflow conditions includes: steady-state flow with a velocity of 0.1 m / s to 2.5 m / s and an interval of 0.1 m / s; regular and irregular waves with a wave height of 0.5 m to 6 m and a period of 3 s to 12 s; and oblique flow with an incident angle of θ = 0° to 90° and an interval of 15°. The above conditions are combined and an offline CFD case library is generated by Latin hypercube sampling.

[0031] With this setup, the above technical solution discloses the complete working condition space and sampling method covered when generating the offline CFD case library; firstly, the variable dimensions are defined as follows: (1) Steady-state flow: velocity 0.1m / s–2.5m / s, step size 0.1m / s → 25 discrete values; (2) Waves: regular waves and irregular waves, wave height 0.5m–6m, period 3s–12s → continuous two-dimensional space; (3) Oblique flow: incident angle θ0°–90°, step size 15° → 7 discrete values; the multidimensional working condition space composed of the above three variables (velocity, wave parameters, incident angle) is filled with Latin hypercube sampling (LHS). LHS ensures that each dimension is evenly distributed and the sample points do not cluster, so that even when the sample size is much smaller than the full factor combination, it can still cover the entire working condition space with a high probability, so as to ensure that any real sea state can be quickly mapped and improve the engineering universality of the method.

[0032] Step S13: Obtain the equivalent resistance parameter based on the flow state of the mesh.

[0033] In the above steps, the equivalent resistance parameters include permeability, drag coefficient, and sheltering factor. Permeability P refers to the "free flow" of fluid through the mesh. P=1 indicates water can pass freely (no mesh), and P=0 indicates complete water blocking (rigid plate). Drag coefficient C_d refers to the "braking force" of the mesh on the water flow. The larger C_d is, the greater the resistance experienced by the mesh at the same flow rate. Sheltering factor S_f refers to the degree to which the front mesh blocks light from the rear mesh. S_f=1 indicates no sheltering, and S_f<1 indicates that the flow velocity of the rear mesh is reduced due to the deceleration of the front mesh. By using the above three "equivalent resistance parameters", the real and complex three-dimensional hydrodynamic behavior of the net is compressed into three dimensionless numbers, which can be directly called by the potential flow model. In the calculation, the potential flow theory model only needs to read (P, C_d, S_f) to reproduce the macroscopic resistance, flow permeability and shading effect of the net on the water body, without having to analyze the millimeter-level mesh details, thus achieving "high precision + low cost" simulation.

[0034] As described above, this embodiment first constructs a CFD model of the porous medium of the netting, then simulates the flow state of the netting under different inflow conditions using the CFD model, and finally obtains the equivalent resistance parameters based on the flow state of the netting. By obtaining the equivalent resistance parameters of the netting under different inflow conditions, it is beneficial to improve the reliability of the equivalent resistance parameters and further improve the calculation accuracy of the hydrodynamics of the net cage.

[0035] As a preferred embodiment of the above, in step S30, the convergence criterion for the bidirectional dynamic coupling is that the difference between the peak values ​​of mooring tension in two adjacent iterations is less than 5%, and the relative change of the L2 norm of the center of gravity displacement of the cage is ≤3%; when the above two criteria are satisfied at the same time, the iteration is terminated and the motion response of the second cage is output.

[0036] With this setup, the difference in peak mooring tension between two adjacent iterations is less than 5%, indicating that the difference in the maximum anchor chain tension between two consecutive iterations does not exceed 5%, suggesting that the mooring system's stress has stabilized and no longer fluctuates significantly. The relative change in the L2 norm of the cage's center of gravity displacement is ≤3%, where the L2 norm, or Euclidean length, measures the overall magnitude of the cage's six-degree-of-freedom displacement vector. A relative change of ≤3% indicates that the cage's trajectory has essentially converged, and the displacement no longer changes significantly. When both of these criteria are met simultaneously, the entire coupled system is considered to have reached statistical stability, the iteration stops, and the final "second cage motion response" is output. This prevents premature shutdown leading to insufficient accuracy and avoids excessive iteration that wastes computational resources.

[0037] As a preferred embodiment of the above, the porous mesh medium CFD model is constructed using a CFD solver, wherein the CFD solver is OpenFOAM; and / or, the potential flow theory model of the cage motion is constructed using a potential flow solver, wherein the potential flow solver is Aqwa. The CFD solver is responsible for constructing and running the porous mesh medium CFD model, calculating the fine flow field and equivalent drag parameters; OpenFOAM is an open-source, cross-platform, general-purpose CFD software that supports custom porous media source terms. The potential flow solver is responsible for constructing the potential flow model of the overall cage motion, quickly providing the six-degree-of-freedom motion response and mooring tension; Aqwa is a commercial-grade offshore engineering potential flow software with built-in libraries for floating bodies, mooring, and waves. This embodiment constructs the porous mesh medium CFD model and the cage motion potential flow theory model using OpenFOAM + Aqwa respectively, which is simple to operate and highly practical.

[0038] Furthermore, the CFD solver and the potential flow solver are coupled via the FMI protocol or a custom script based on Python / Bash. The FMI protocol (Functional Mock-up Interface) is an industry standard that encapsulates the CFD and potential flow as "black box modules," exchanging boundary conditions, displacements, tensions, and other data through a standard interface. Its advantages include cross-platform compatibility and cross-language compatibility, allowing direct integration into any platform that supports FMI (such as OpenFOAM + Aqwa). The Python / Bash custom script uses a scripting language to periodically read and write the input / output files of the two solvers (or call APIs) to achieve data transfer. Its advantages include zero dependencies, customizable timing, and the ability to run locally, in the cloud, or within a container. In practice, technicians can choose the appropriate method to achieve data coupling between the CFD solver and the potential flow solver based on their own circumstances, offering high flexibility.

[0039] This invention also proposes a hydrodynamic calculation system for a net cage, including a processor and a memory. The memory stores a computer program, characterized in that the computer program can be executed by the processor to implement the hydrodynamic calculation method for a net cage as described in any of the above embodiments. Specific steps of the hydrodynamic calculation method for the net cage can be referred to the above embodiments. Since this hydrodynamic calculation system for a net cage adopts all the technical solutions of all the above embodiments, it possesses at least all the beneficial effects brought about by the technical solutions of the above embodiments, and will not be elaborated further here.

[0040] To address the aforementioned technical problems, this invention proposes a readable storage medium storing a computer program, characterized in that the computer program can be read to implement the cage hydrodynamic calculation method described in any of the above embodiments. Specific steps of the cage hydrodynamic calculation method can be referred to the above embodiments. Since this cage hydrodynamic calculation system adopts all the technical solutions of all the above embodiments, it possesses at least all the beneficial effects brought about by the technical solutions of the above embodiments, and will not be elaborated upon further here.

[0041] It should be noted that the hydrodynamic calculation method, system, and other contents of the readable storage medium disclosed in this invention are prior art and will not be described in detail here.

[0042] The above are merely optional embodiments of the present invention and do not limit the patent scope of the present invention. Any application of the present invention directly or indirectly in other related technical fields is included within the patent protection scope of the present invention.

Claims

1. A method for calculating the hydrodynamic forces on a net cage, characterized by, The method comprises the following steps: constructing a net cloth porous medium CFD model to obtain equivalent resistance parameters of the net cloth; constructing a net cage motion potential flow theory model, embedding the equivalent resistance parameters into the net cage motion potential flow theory model to obtain a first net cage motion response; embedding the first net cage motion response into the net cloth porous medium CFD model to perform bidirectional dynamic coupling of the net cloth porous medium CFD model and the net cage motion potential flow theory model, and obtaining a second net cage motion response through multiple bidirectional dynamic couplings; calculating net cage hydrodynamic force according to the second net cage motion response.

2. The net cage hydrodynamic calculation method of claim 1, wherein: In the step of constructing the net cloth porous medium CFD model to obtain the equivalent resistance parameters of the net cloth, the following steps are included: constructing the net cloth porous medium CFD model; simulating the flow state of the net cloth under different inflow conditions through the net cloth porous medium CFD model; obtaining the equivalent resistance parameters according to the flow state of the net cloth.

3. The net cage hydrodynamic calculation method of claim 2, wherein: In the step of constructing the net cloth porous medium CFD model, the net cloth porous medium CFD model adopts local overlapping grid or immersed boundary-porous medium coupling algorithm to maintain y*≤1 boundary layer solution when the thickness of the net cloth is ≤3mm; And the net cloth porous medium CFD model uses adaptive grid encryption in the net cloth area, and the grid encryption trigger condition is velocity gradient u|≥0.2U ∞ / L_ref.

4. The net cage hydrodynamic calculation method of claim 2, wherein: in the step of simulating the flow state of the net cloth under different inflow conditions through the net cloth porous medium CFD model, the simulation of different inflow conditions includes: steady flow with a flow rate of 0.1m / s~2.5m / s at an interval of 0.1m / s; regular wave and irregular wave with a wave height of 0.5m~6m and a period of 3s~12s; oblique flow with an incident angle θ=0°~90° at an interval of 15°; combining the above working conditions to generate an offline CFD example library through Latin hypercube sampling.

5. The net cage hydrodynamic calculation method of claim 2, wherein: In the step of obtaining the equivalent resistance parameters according to the flow state of the net cloth, the equivalent resistance parameters include water permeability, resistance coefficient and shielding effect factor.

6. The net cage hydrodynamic calculation method of claim 1, wherein: In the step of obtaining the second net cage motion response through multiple bidirectional dynamic couplings, the convergence criterion of the bidirectional dynamic coupling is that the peak value difference of mooring tension of adjacent two iterations is less than 5%, and the relative change of L2 norm of the center of gravity displacement of the net cage is ≤3%; when the above two criteria are met at the same time, the iteration is terminated and the second net cage motion response is output.

7. A net cage hydrodynamic calculation method according to any one of claims 1 to 6, characterized by: The net cloth porous medium CFD model is constructed by a CFD solver, wherein the CFD solver is OpenFOAM; and / or, the net cage motion potential flow theory model is constructed by a potential flow solver, wherein the potential flow solver is Aqwa.

8. The net cage hydrodynamic calculation method of claim 7, wherein: The CFD solver and the potential flow solver adopt FMI protocol or Python / Bash-based custom script to realize data coupling.

9. A net cage hydrodynamic calculation system comprising a processor and a memory, the memory having stored therein a computer program, characterized in that, The computer program can be executed by a processor to implement the net cage hydrodynamic force calculation method according to any one of claims 1 to 8.

10. A readable storage medium, storing a computer program, characterized in that, The computer program can be read to implement the net cage hydrodynamic force calculation method according to any one of claims 1 to 8.

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