Numerical simulation method for offshore platform pile leg

Abstract

The invention relates to ocean engineering, in particular to a numerical simulation method of an offshore platform pile leg, which improves the accuracy of wave surface height change description and wave behavior description by adding complex correction terms for a wave surface function and a wave velocity field. A parallel computing strategy and an optimized numerical method are introduced, so that the computing efficiency and the computing speed are effectively improved, a super computer and high-performance computing resources are utilized, the computing period is shortened, the cost is reduced, and meanwhile, the accuracy and the stability of a simulation result are ensured; and meanwhile, through refined grid division and an efficient numerical method, the space resolution and the time resolution of simulation are improved, so that the stress condition of the structure and the influence of waves are accurately predicted.

Description

Technical Field

[0001] This case involves marine engineering, and in particular, involves a high-precision numerical simulation method suitable for multi-shaped offshore platform pile legs. Background Art

[0002] In the field of marine engineering, especially in the design and evaluation of marine structures such as platforms, bridges, dams, etc. that are affected by waves, numerical simulation of fluid dynamics plays an important role. These structures must be able to withstand complex loads from waves and currents in the marine environment, so accurately predicting the impact of waves on structures has become one of the key tasks in the design process. Summary of the invention

[0003] The purpose of this case is to propose a numerical simulation method suitable for multi-shaped offshore platform pile legs, so as to accurately simulate the wave behavior and structural forces in the complex marine environment wave-structure interaction, thereby ensuring the safety and stability of structures such as platforms, bridges, dams, etc. that are subject to complex influences of waves and currents. To achieve the above purpose, the specific technical solution of this case is as follows.

[0004] In a first aspect, a numerical simulation method for an offshore platform leg is provided. In solving the control equation, a static boundary method (SBM) is used to generate a regular wave. The wave surface function of the regular wave is:

[0005]

[0006] in: is a correction term to improve the accuracy of describing wave behavior;

[0007] The velocity field of the regular wave is composed of the velocity u in the wave propagation direction and the velocity w perpendicular to the wave propagation direction, which are calculated using the following formulas:

[0008]

[0009] in: and All are correction terms to improve the accuracy of describing velocity distribution;

[0010] In solving, the entire calculation area is divided into a plurality of sub-calculation areas, and each sub-calculation area uses an independent processor to perform calculations, so that the plurality of sub-calculation areas perform parallel calculations;

[0011] In the above formula, H is the wave height, x is the current position, k is the wave number, d is the water depth, cosh represents the hyperbolic cosine function, sinh is the hyperbolic sine function, t is the time step, λ is the incident wavelength, z is the vertical position from the water surface to the bottom of the water, u is the speed in the direction of wave propagation, and w is.

[0012] In one implementation of the above technical solution, the method sequentially establishes grid models of different shapes for the entire calculation area, and in each grid model, the area where the wave free surface is located is locally encrypted, so as to select the optimal model and parameter setting through numerical comparison.

[0013] In one implementation of the above technical solution, the shapes include cylinders, triangular prisms, and rounded triangular prisms, which can be adapted to various precision requirements.

[0014] In one implementation of the above technical solution, the control equation is as follows:

[0015]

[0016] in, is the velocity vector of the fluid, represents the divergence operation, represents the acceleration due to gravity; represents the gradient, P represents the pressure, σ represents the surface tension coefficient, represents curvature; ξ represents the damping coefficient, x represents the current position, x in Indicates the starting position of the damping zone, and L indicates the length of the damping zone;

[0017] The absorption coefficient δ is:

[0018] The density ρ and dynamic viscosity coefficient μ are as follows:

[0019] ρ1 represents the density of water, ρ2 represents the density of air, μ1 represents the viscosity of water, u2 represents the viscosity of air, and α is the volume fraction.

[0020] In a second aspect, a computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the above methods.

[0021] Beneficial technical effects of this case: By adopting the simulation method proposed in this case, wave behavior and wave speed distribution can be accurately predicted, which is helpful to accurately calculate the forces on the structure, including but not limited to: accurately capturing the interaction between waves and the surface of the structure, including pressure distribution, mechanical response, etc., especially wave loads under large-scale and complex wave conditions; being able to numerically simulate complex fluid flow phenomena in the marine environment, such as wave propagation, water turbulence and other complex flow fields, and ensure the accuracy and reliability of the simulation results; being able to improve the computational efficiency of numerical simulation, reduce computing costs and time, and ensure the accuracy and stability of simulation results; being able to ensure the consistency of numerical simulation results with actual engineering conditions, providing a reliable basis for structural design, safety assessment and operation, and being able to be actually applied in engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0023] Figure 1 , one Schematic diagram of numerical simulation comparison using three models of cylinder, triangular prism and rounded triangular prism in the embodiment.

[0024] Figure 2(a) , one Schematic diagram of the meshing results of the entire calculation area in this implementation method.

[0025] FIG. 2( b ) is a partial schematic diagram of FIG. 2( a ).

[0026] Figure 3 , one Schematic diagram of scalability analysis of the method of this case in the embodiment, where (a) is the acceleration ratio and (b) is the efficiency.

[0027] Figure 4 , one Schematic diagram of comparison of wave run-up ratios (η / A) under different r / R changes obtained at different detection positions in the embodiment with the results of other published literature (H=0.422m).

[0028] Figure 5 , one Schematic diagram of comparison of wave run-up ratios (η / A) under different r / R changes obtained at different detection positions in the embodiment with the results of other published literature (H=0.79m).

[0029] Figure 6 , one Comparison of single-sided wave climbing in two implementation modes, where (a) H / λ=1 / 30; (b) H / λ=1 / 16.

[0030] Figure 7 , one Schematic diagram of wave run-up ratio (η / A) under different r / R changes obtained at different monitoring positions for three models with circular, triangular and rounded triangle cross sections in the embodiment (H=0.422m).

[0031] Figure 8 , oneSchematic diagram of wave run-up ratio (n / A) under different r / R changes obtained at different monitoring positions for three models with circular, triangular, and rounded triangle cross sections in the implementation method (H = 0.79m). DETAILED DESCRIPTION

[0032] The English and Chinese versions of the attached drawings in this case and their meanings.

[0033]

[0034] The existing technology has the following main disadvantages when simulating the impact of waves on structures in marine environments:

[0035] 1. Insufficient precision

[0036] Traditional numerical simulation methods have limited accuracy in capturing the dynamic behavior of waves in complex marine environments. In particular, when dealing with the water-air interface and the interaction between structures and waves, it is often impossible to accurately predict the wave run-up and forces on structures.

[0037] 2. Low computational efficiency

[0038] Numerical simulations in complex marine environments usually require high-precision meshing and large-scale computing resources, but existing methods often fail to meet actual engineering needs in terms of computational efficiency. Long computational cycles and high costs limit the breadth and practicality of simulation methods.

[0039] 3. Model selection and applicability limitations

[0040] Existing methods have limitations in selecting appropriate numerical models (such as structural models) and applicability assessment. Most methods are limited to cylindrical pile legs. Different structural shapes and wave conditions may lead to different simulation results, but selecting appropriate models and parameter settings often requires experience and a large number of experimental verifications.

[0041] Based on this, this case proposes a numerical simulation method for offshore platform pile legs, which improves the accuracy of the description of wave surface height changes and wave behavior by adding complex correction terms to the wave surface function and wave velocity field; and effectively improves the calculation efficiency and speed by introducing parallel computing strategies and optimized numerical methods, and uses supercomputers and high-performance computing resources to shorten the calculation cycle and reduce costs, while ensuring the accuracy and stability of the simulation results; at the same time, through refined grid division and efficient numerical methods, the spatial and temporal resolution of the simulation is improved, so as to accurately predict the stress conditions and wave effects of the structure. According to the specific wave conditions and engineering requirements, the optimal model and parameter settings are recommended through comparative analysis of multiple structural models. The reliability and repeatability of the simulation results are ensured through systematic model verification and experimental data comparison. The method proposed in this case can be used to provide more reliable technical support and solutions for the fields of marine structure design, marine resource development and environmental protection.

[0042] The following will provide a clear and complete description of how to implement the technical solution of this case in conjunction with the accompanying drawings.

[0043] (I) Establishing the control equation

[0044] Simulation of the fluid around the pile legs. In the simulation, two phases, water and air, are involved. Assuming that both water and air are incompressible fluids, the governing equations for the flow of three-dimensional incompressible viscous fluids are established. The governing equations for the flow of three-dimensional incompressible viscous fluids include the mass conservation equation and the Navier-Stokes equations, which are solved by using the open source field OpenFOAM operations and runs.

[0045] Specifically, the mass conservation equation is expressed as follows:

[0046]

[0047] in, is the velocity vector of the fluid, represents the divergence operation. This equation ensures that the density of the fluid remains constant as it flows.

[0048] The Navier-Stokes equations are shown below:

[0049]

[0050] in, Represents the acceleration due to gravity. represents the gradient. P represents the pressure, ρ represents the density, μ represents the dynamic viscosity coefficient. σ represents the surface tension coefficient, Represents curvature. Represents surface tension. is a wave damping term, which is used to eliminate the influence of reflected waves. The absorption coefficient δ is defined as follows.

[0051]

[0052] Among them, ξ represents the damping coefficient (constant), x represents the current position, and x in Indicates the starting position of the damping zone, and L indicates the length of the damping zone.

[0053] The volume of fluid (VOF) method is used to capture the water-air interface. This method distinguishes different states of fluid by the volume fraction α, which is defined as follows:

[0054]

[0055] The volume fraction governing equation is as follows:

[0056]

[0057] When solving, the two fluids are treated as one fluid, satisfying the following equation. The density ρ and viscosity μ of the fluid are calculated by the weight function of the volume fraction α, which is defined as follows:

[0058]

[0059] Among them, ρ1 represents the density of water, ρ2 represents the density of air, μ1 represents the viscosity of water, and μ2 represents the viscosity of air.

[0060] (II) Given boundary conditions and initial conditions

[0061] The static boundary method (SBM) is used to generate regular waves, fix the incident wave boundary, and prescribe the velocity and free surface position of the water particles according to the corresponding wave theory.

[0062] Using Stokes waves at fixed inlet wave boundaries, more complex correction terms are added to more accurately describe the behavior of waves. The regular wave profile is represented by η, and the expression for η is:

[0063]

[0064] Where H is the wave height, k is the wave number, d is the water depth, cosh is the hyperbolic cosine function, sinh is the hyperbolic sine function, t is the time step, λ is the incident wavelength, and ω is the angular frequency.

[0065] The wave velocity field is defined as follows: u represents the velocity in the direction of wave propagation, and w represents the velocity perpendicular to the direction of wave propagation. u and w are The two components of u and w can be expressed as:

[0066]

[0067] Where T is the wave period. z is the vertical position from the water surface to the bottom of the water, which together with the wave number k and the water depth d describes the velocity distribution of waves under different water depth conditions.

[0068] (III) Dividing the computational grid

[0069] The calculation area is meshed, and in order to more accurately capture the dynamic behavior of the waves and obtain more precise results, the area where the wave free surface is located is locally encrypted, and the total number of meshes reaches tens of millions.

[0070] In one embodiment, three models, namely, a cylinder, a triangular prism, and a rounded triangular prism, are used for numerical simulation comparison. The cross-sections of the three models are shown in FIG. Figure 1 Figure 2(a) shows a grid division method for the entire calculation area. The position of the initial free interface is set to z = 0, and the grid refinement area is in the z-axis range of (-2, 2). The grid refinement area completely covers the vibration range of the waves in two working conditions (H = 0.422m and H = 0.79m). Figure 2(b) shows the local details of the grid.

[0071] (IV) Establishing discrete equations

[0072] The governing equations and fluid volume law equations are discretized by the finite volume method (FVM).

[0073] Specifically, the PIMPLE method, which combines the Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) and Pressure-Implicit with Splitting of Operators (PISO), is used to solve the coupling of velocity and pressure. For the time derivative, the implicit Euler scheme is used for time discretization. For the gradient term, Gaussian linear interpolation is used. Gaussian linear interpolation is used for the discretization of the Laplace term. The upwind scheme is used to handle the convection term. A Gaussian linear correction scheme is used to handle the viscous diffusion term. A Gaussian interface compression scheme is used to discretize the volume fraction equation to accurately capture the free surface.

[0074] (V) Discrete initial conditions and boundary conditions

[0075] Based on the divided grid, the above initial conditions and boundary conditions are distributed to the corresponding nodes in a discrete manner.

[0076] (VI) Given control parameters

[0077] The control parameters are set as follows: the density of water is 1000kg / m 3 , viscosity is 10 -6 m2 / s; the density of air is 1kg / m 3 , the viscosity is 1.48×10 -5 m 2 / s; the surface tension coefficient is 0.07N / m.

[0078] The time step deltaT=0.001, and the adjustableRunTime is set to automatic adjustment.

[0079] The convergence accuracy of the velocity-pressure coupling algorithm PIMPLE is 10 -6 .

[0080] (VII) Solution

[0081] The discrete equations are iteratively solved within a given time step using the discrete initial and boundary conditions.

[0082] A large number of numerical simulation studies have shown that the pressure solver uses Geometric Algebraic Multi Grid (GAMG), the pre-solver uses GaussSeidel, the velocity solver uses Stabilised Preconditioned (bi-) Conjugate Gradient (PBiCGStab), and the pre-solver uses Diagonal Incomplete-LU (DILU), which can obtain good results. The specific test results are shown in Table 1.

[0083] Table 1 Solution time of linear algebra solver

[0084] Test Cases Pressure Solver Preconditioner / smooth Velocity Solver Pre-regulator Execution time(s) Test 1 GAMG Gauss Seidel PBiCGStab DILU 155.12 Test 2 GAMG symGaussSeidel PBiCGStab DILU 157.54 Test 3 GAMG DIC PBiCGStab DILU 160.10 Test 4 GAMG FDIC PBiCGStab DILU 159.07 Test 5 PCG DIC PBiCGStab DILU 173.89 Test 6 PCG FDIC PBiCGStab DILU 170.82

[0085] In parallel computing, the scalability test of the method is very important. The scalability of the method was tested by using two sets of grids with different densities and tested on 64, 128, 256, 512 and 1024 processor cores, as shown in Table 2 and Figure 3 .

[0086] In terms of strong scalability, the simulation time decreases with the number of cores, and the overall speedup increases with the number of cores, indicating that the method has robust performance with increasing computing resources. Although the efficiency decreases slightly with the increase in the number of cores, it is still relatively high even in the case of a maximum of 1024 cores, which may be attributed to the communication and synchronization overhead introduced by parallelization.

[0087] In terms of weak scalability, we use a fixed grid size of 1.0×10 per core. 4 and 1.1×10 4We ran tests between 1 and 2 and observed that the execution time varied as expected with weak scalability. It scales with increasing problem size and number of cores. The efficiency trend suggests that the approach effectively utilizes more computing resources when handling larger problems.

[0088] Table 2 Method scalability analysis

[0089]

[0090] In parallel computing, OpenFOAM is used to decompose the computational area and divide the entire computational domain into multiple sub-computational domains. These sub-computational domains are assigned to independent processors on the supercomputer, and each processor uses a copy of the solver to calculate its assigned sub-computational domain, thereby realizing parallel computing of the entire computational domain. During the calculation process, information is exchanged between the processors to collaboratively solve the entire computational domain. In each time step of each calculation cycle, the calculation results of each sub-computational domain are collected, and then merged and processed on the supercomputer to finally obtain the global result of the entire computational domain. This parallel computing strategy effectively improves the computing efficiency and makes full use of the parallel processing capabilities of the supercomputer.

[0091] Finally, the results of parallel calculations performed by OpenFOAM are processed using data visualization software such as ParaView and Tecplot. This includes visualization of key physical quantities such as velocity and pressure in the calculation area. This visualization helps to optimize the calculation model and parameters, improve simulation efficiency, and more comprehensively interpret the simulation results.

[0092] As can be seen from the above, the above process describes a high-precision fluid dynamics numerical simulation method for structures in marine environments, including comparative analysis using different structural models, and the steps and methods of numerical simulation using the open source field OpenFOAM. This method can be applied to wave response prediction and structural design optimization when designing marine engineering structures (such as pile legs), and can be applied to marine engineering, marine resource development and other fields to improve the safety and economy of engineering design. This method improves the efficiency and speed of numerical simulation through efficient meshing and parallel computing strategies.

[0093] (II) Analysis of method application

[0094] Figure 4 and Figure 5The comparison of the wave climb-up ratio (η / A) obtained at different monitoring locations under different r / R changes and the results of other published literature is shown, where r represents the distance from the monitoring point to the center of a single cylinder, and R is the radius of the cylinder cross-section circle. The wave climb-up ratio refers to the degree of increase in the wave height on a specific structure (such as seawall, dam, etc.) during the propagation of the wave. The wave climb-up ratios of the wave monitoring points in radial A and radial B were analyzed at two wave heights of H=0.422m and H=0.79m. In the case of wave height H=0.422m, the wave climb-up ratio obtained by the static boundary method (SBM) of this method is highly consistent with the results of other numerical methods in Chen et al. (2021), Cao, Wan (2017) and Nielsen (2003). As the wave height H increases to 0.79, the wave climbs monitored in previously published articles differ greatly from the values ​​reported in most literature, such as radial A of the PBM method Cao et al. (2011) and radial B of the BEM method Nielsen (2003). This phenomenon is caused by the increase in wave height and the increase in wave nonlinearity. However, the wave climb ratio calculated by this method is highly consistent with the numerical results of most literature, and the error is within a reasonable range. The larger errors occur at points A3 and A4 in radial A. The error between point A3 and the MSM method Chen et al. (2021) is 5.14%, and the error between point A4 and the PBM method Cao et al. (2011) is 4.00%.

[0095] Figure 6 The comparison results of the wave climb-up ratio (η / A) of a truncated cylinder are shown. In this study, the distribution of η / A with the radial angle θ obtained by the static boundary method (SBM) is highly consistent with the experimental and numerical results of Chen et al. (2021), Cao, Wan (2017) and Nielsen (2003). The minimum wave climb-up ratio monitored under both wave conditions is at the side and rear of the cylinder (θ = 45°). Comparative analysis with the numerical results of published articles at various different angles shows the accuracy and stability of the proposed method, and the results are convincing.

[0096] Figure 7 and Figure 8The wave climb-up ratio (η / A) of three models with circular, triangular and rounded triangle cross-sections under different r / R changes at different monitoring positions is shown. The wave climb-up ratios of the wave monitoring points in radial A and radial B of the three models are analyzed under two wave heights of H = 0.422m and H = 0.79m. Under the condition of wave height H = 0.422m, the wave climb-up in radial A and radial B of triangular prism and rounded triangular prism is lower than that of circular cylinder. Specifically, for triangular prism, the wave climb-up of the four monitoring points in radial A is reduced by about 13.74% on average compared with that of circular cylinder, while the wave climb-up of the four monitoring points in radial B is reduced by about 5.38% on average; for rounded triangular prism, the wave climb-up of the four monitoring points in radial A is reduced by about 16.11% on average compared with that of circular cylinder, while the wave climb-up of the four monitoring points in radial B is reduced by about 7.99% on average. The case of wave height H = 0.79m is similar to the case of wave height H = 0.422m, with the same trend.

[0097] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method of the present invention can be implemented by means of software plus necessary general hardware, and of course can also be implemented by special hardware including special integrated circuits, special CPUs, special memories, special components, etc. In general, all functions performed by computer programs can be easily implemented by corresponding hardware, and the specific hardware structures used to implement the same function can also be various, such as analog circuits, digital circuits or special circuits, etc. However, for the present disclosure, software program implementation is a better implementation method in most cases.

[0098] Although the implementation scheme of the present case is described above in conjunction with the accompanying drawings, the present case is not limited to the above specific implementation scheme, and can be applied to numerical simulations of wave dynamic responses of structures including but not limited to offshore platforms, dams, bridges, etc. The above specific implementation scheme is merely illustrative and instructive, and not restrictive. Under the guidance of this specification and without departing from the scope of protection of the claims of the present case, ordinary technicians in this field can also make many forms, all of which belong to the scope of protection of the present case.

Claims

1. A numerical simulation method for offshore platform pile legs, characterized in that: In solving the control equation, the method uses the static boundary method (SBM) to generate a regular wave, and the wave surface function of the regular wave is: in: is a correction term to improve the accuracy of describing wave behavior; The velocity field of the regular wave is composed of the velocity u in the wave propagation direction and the velocity w perpendicular to the wave propagation direction, which are calculated using the following formulas: in: and All are correction terms to improve the accuracy of describing velocity distribution; In solving, the entire calculation area is divided into a plurality of sub-calculation areas, and each sub-calculation area uses an independent processor to perform calculations, so that the plurality of sub-calculation areas perform parallel calculations; In the above formula, H is the wave height, x is the current position, k is the wave number, d is the water depth, cosh represents the hyperbolic cosine function, sinh is the hyperbolic sine function, t is the time step, λ is the incident wavelength, z is the vertical position from the water surface to the bottom of the water, u is the speed in the direction of wave propagation, and w is.

2. The method according to claim 1, characterized in that The method sequentially establishes grid models of different shapes for the entire calculation area, and in each grid model, the area where the wave free surface is located is locally encrypted, so as to select the optimal model and parameter setting through numerical comparison.

3. The method according to claim 2, characterized in that The shapes include cylinder, triangular prism and rounded triangular prism.

4. The method according to claim 1, characterized in that The control equation is as follows: in, is the velocity vector of the fluid, represents the divergence operation, represents the acceleration due to gravity; represents the gradient, P represents the pressure, σ represents the surface tension coefficient, represents curvature; ξ represents the damping coefficient, x represents the current position, X in Indicates the starting position of the damping zone, and L indicates the length of the damping zone; The absorption coefficient δ is: The density ρ and dynamic viscosity coefficient μ are as follows: ρ1 represents the density of water, ρ2 represents the density of air, μ1 represents the viscosity of water, μ2 represents the viscosity of air, and α is the volume fraction.

5. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 4.

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